JP5272775B2 - Electronic still camera - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an electronic still camera capable of acquiring desirable images on composition and from the viewpoint of pictures. <P>SOLUTION: The electronic still camera is provided with: a face detection part which detects a face from a through-the-lens-image to be fetched; an expression identification part which identifies the expression of the face detected by the face detection part: an imaging part which acquires a main image when it is identified that the expression of the face is a smiling face by the expression identification part; an object extraction part which extracts an object to be a smiling face as a primary object from the main image; and an image processing part which performs at least one of processing of vignetting regions of the main image except for the region of the primary object, painting out the regions of the main image except for the region of the primary object in monochrome, or generating a segmented image by segmenting predetermined composition including the primary object in the main image. <P>COPYRIGHT: (C)2010,JPO&amp;INPIT

Description

  The present invention relates to an electronic still camera that acquires an image.

  2. Description of the Related Art Conventionally, cameras that detect a subject's smile and automatically capture an image are known. For example, the camera disclosed in Patent Document 1 determines the image signal when the facial expression detected from the image signal is a smile during the period until the image signal obtained by imaging is recorded on the recording medium. Automatically record on the recording medium.

  However, the above-described camera automatically records an image signal when a smile is detected regardless of the background. Therefore, the obtained image may include a passing person or an unknown person. Such an image is not preferable in terms of composition or pictorially, and there is a possibility that a precious smile is ruined.

  SUMMARY An advantage of some aspects of the invention is that it provides an electronic still camera capable of acquiring a compositionally or pictorially preferable image.

The electronic still camera of the present invention includes a face detection unit that detects a face from a captured through image, a facial expression identification unit that identifies a facial expression detected by the face detection unit, and the facial expression by the facial expression identification unit. Is identified as a smile, an imaging unit that acquires a main image, a subject extraction unit that extracts a subject that is a smile from the main image as a main subject, and the main image other than the main subject An image processing unit that performs a process of blurring the area of the image, and an evaluation value calculation unit that calculates a smile evaluation value indicating the degree of smile of the main subject, the image processing unit according to the smile evaluation value, It is characterized in that at least one of a blurring shape and a blurring degree used for the blurring process is determined.
Further, the subject extraction unit extracts, as the main subject, the subject having the highest smile evaluation value calculated by the evaluation value calculation unit when a plurality of subjects to be smiling are extracted from the main image. It is characterized by.

The electronic still camera of the present invention includes a face detection unit that detects a face from a captured through image, a facial expression identification unit that identifies facial expressions detected by the face detection unit, and the facial expression recognition unit that detects the face. When the facial expression is identified as a smile, an imaging unit that acquires a main image, a subject extraction unit that extracts a subject that becomes a smile from the main image as a main subject, and the main image with respect to the main image An image processing unit that performs a process of blurring a region other than the subject, and a luminance calculation unit that calculates the luminance of the region other than the main subject, the image processing unit according to the luminance calculated by the luminance calculation unit Thus, at least one of a blur shape and a blur degree used for the blur processing is determined.

  The electronic still camera of the present invention includes a face detection unit that detects a face from a captured through image, a facial expression identification unit that identifies facial expressions detected by the face detection unit, and the facial expression recognition unit that detects the face. When the facial expression is identified as a smile, an imaging unit that acquires a main image, a subject extraction unit that extracts a subject that becomes a smile from the main image as a main subject, and the main image with respect to the main image An image processing unit that performs processing to blur a region other than the subject, and an estimation unit that estimates at least one of the age and gender of the main subject, the image processing unit according to an estimation result by the estimation unit, It is characterized in that at least one of a blurring shape and a blurring degree used for the blurring process is determined.

An evaluation value calculating unit configured to calculate a smile evaluation value indicating the degree of smile; the subject extracting unit is configured to output a plurality of subjects that are smiling from the main image by the evaluation value calculating unit; A subject with the highest calculated smile evaluation value is extracted as the main subject.
  In addition, a ratio calculating unit that calculates a ratio of the smile area in the main image is provided, and the subject extraction unit occupies the main image when a plurality of the subjects to be smiling are extracted from the main image. The subject having the highest smile area ratio is extracted as the main subject.

Further, after extracting the feature quantity information indicating the feature quantity of the face and the face feature quantity detected by the face detection section, whether or not the extracted feature quantity matches the feature quantity information A face identifying unit that determines whether or not the image capturing unit determines that the feature amount of the face detected by the face identifying unit matches the feature amount information stored in the storage unit The acquisition of the main image is prohibited when the acquisition of the main image is performed and a face that is determined not to match the feature amount and the feature amount information is included.

Further, after extracting the feature quantity information indicating the feature quantity of the face and the face feature quantity detected by the face detection section, whether or not the extracted feature quantity matches the feature quantity information A face identification unit that performs such determination, and a face determined by the face identification unit that the feature amount detected by the face identification unit and the feature amount information stored in the storage unit do not match, The imaging unit can select whether or not to acquire the main image.
  In this case, when the imaging unit selects to acquire the main image, when the facial smile evaluation value determined to match the feature amount and the feature amount information is equal to or greater than a threshold, the book An image is acquired.

Further, after extracting the feature quantity information indicating the feature quantity of the face and the face feature quantity detected by the face detection section, whether or not the extracted feature quantity matches the feature quantity information A face identification unit for determining whether or not the face detected from the through image is blurred, and a sharpness determination unit for determining whether the face detected from the through image is blurred. When a face determined to not match the feature amount information stored in the storage unit is included and the face is blurred, the imaging unit determines whether to acquire the main image. It is possible to select.

  Further, after extracting the feature quantity information indicating the feature quantity of the face and the face feature quantity detected by the face detection section, whether or not the extracted feature quantity matches the feature quantity information A face identification unit that determines whether the feature amount detected by the face identification unit does not match the feature amount information stored in the storage unit. A first mode in which the main image is not acquired by the imaging unit, and a second mode in which whether to acquire the main image is selected.

The electronic still camera of the present invention includes a face detection unit that detects a face from a captured through image, a facial expression identification unit that identifies facial expressions detected by the face detection unit, and the facial expression recognition unit that detects the face. When the facial expression is identified as a smile, an imaging unit that acquires a main image, a subject extraction unit that extracts a subject that becomes a smile from the main image as a main subject, and the main image with respect to the main image Processing to blur a region other than the subject, processing to paint the region other than the main subject in a single color on the main image, or cut out a predetermined composition including the main subject from the main image to generate a cutout image In addition to an image processing unit that performs at least one of the processes, a storage unit that stores feature amount information indicating a facial feature amount, and a facial feature amount detected by the face detection unit And a face identification unit that determines whether the extracted feature quantity matches the feature quantity information after the extraction, and the subject extraction unit extracts a plurality of subjects that become the smile from the main image In this case, the face identifying unit extracts a subject having a feature amount that matches the feature amount information as a main subject.

The electronic still camera of the present invention includes a face detection unit that detects a face from a captured through image, a facial expression identification unit that identifies facial expressions detected by the face detection unit, and the facial expression recognition unit that detects the face. When the facial expression is identified as a smile, an imaging unit that acquires a main image, a subject extraction unit that extracts a subject that becomes a smile from the main image as a main subject, and the main image with respect to the main image Processing to blur a region other than the subject, processing to paint the region other than the main subject in a single color on the main image, or cut out a predetermined composition including the main subject from the main image to generate a cutout image Among the processing, an image processing unit that performs at least one processing, a storage unit that stores feature amount information indicating a feature amount of a face, and a facial feature amount detected by the face detection unit A face identifying unit that determines whether or not the extracted feature value matches the feature amount information, and a sharpness determination unit that determines whether or not the face detected from the through image is blurred And a face determined to be inconsistent with the feature amount detected by the face identification unit and the feature amount information stored in the storage unit, and the face is blurred In addition, the imaging unit can select whether or not to acquire the main image.

  According to the electronic still camera of the present invention, a compositionally or pictorially preferable image can be acquired.

It is a block diagram which shows the structure of the electronic still camera 1 in 1st Embodiment of this invention. It is a figure which shows the luminance distribution of the luminescent point before and behind a blurring process. It is a figure which shows the example of a blurring shape. 4 is a flowchart illustrating an operation of the control unit 10 during imaging in the smile mode in the electronic still camera 1. It is a figure which shows the example of a main image or a composition frame. It is a table | surface which shows the relationship between the main to-be-photographed object A or the background area | region B, and a blurring degree or a blurring shape. It is a flowchart which shows operation | movement of the control part 10 at the time of imaging by the "smile mode 1" in the electronic still camera 1 of 2nd Embodiment. It is a flowchart which shows operation | movement of the control part 10 at the time of imaging by the "smile mode 2" in the electronic still camera 1 of 2nd Embodiment. It is a figure which shows the example of the display part 15 at the time of the imaging in the electronic still camera 1 of 2nd Embodiment. FIG. 10 is a diagram illustrating an example of the display unit 15 when a user sets in advance whether or not to acquire a main image even when a non-registered person exists in step S306 in FIG. 9.

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a configuration of an electronic still camera 1 according to the first embodiment of the present invention. As shown in FIG. 1, the electronic still camera 1 includes an imaging lens 2, an imaging device 3, an A / D conversion unit 4, a buffer memory 5, an image processing unit 6, a compression / decompression processing unit 7, a control unit 10, and a display unit 15. A memory 16, an operation unit 17, a recording I / F unit 20, a recording medium 21, and a bus 22.

  The imaging lens 2 forms a subject image on the imaging surface of the imaging element 3. In addition to the imaging lens 2, an imaging optical system including a plurality of lenses such as a zoom lens and a focus lens may be used. The imaging element 3 photoelectrically converts the subject light that has passed through the imaging lens 2 and outputs analog image signals corresponding to R, G, and B colors. In the photographing mode, the image sensor 3 performs thinning readout at predetermined intervals to obtain a through image. Thereafter, the image sensor 3 acquires the main image when the release button 18 is fully pressed. Further, the image pickup device 3 automatically acquires the main image when the facial expression identification unit 12 described later identifies a smile from the through image. Hereinafter, a mode in which a main image is automatically acquired when a smile is identified will be described as a “smile mode”.

  An image signal output from the image sensor 3 is input to the A / D converter 4. The A / D converter 4 performs A / D conversion on the analog image signal output from the image sensor 3 and converts the analog image signal into a digital image signal. The digital image signals are collected into one frame and recorded in the buffer memory 5 as image data. The buffer memory 5 temporarily records image data in the pre-process and post-process of image processing by the image processing unit 6.

  The image processing unit 6 performs image processing on the image data stored in the buffer memory 5. Examples of the image processing include well-known white balance adjustment, color interpolation, gradation conversion processing, and contour enhancement processing. Further, the image processing unit 6 performs a blurring process and a single color filling process, which will be described later, on the main image and the image recorded on the recording medium 21. Further, the image processing unit 6 may cut out a region having a predetermined composition from the main image or an image recorded on the recording medium 21 using a composition frame stored in advance in the memory 16 to generate a cut-out image. it can. The composition frame will be described later. The compression / decompression processing unit 7 includes an analysis unit 8 and a compression unit 9. The analysis unit 8 performs spatial frequency analysis on the image data. The compression unit 9 executes compression / decompression processing in JPEG (Joint Photographic Experts Group) format.

  The control unit 10 performs overall control of the electronic still camera 1 according to a predetermined sequence program, and executes various calculations (AF, AE, etc.) necessary for imaging. The control unit 10 includes a face detection unit 11, a facial expression identification unit 12, a face identification unit 13, and a subject extraction unit 14. The face detection unit 11 extracts feature points from the through image, the main image, and the image recorded on the recording medium 21 to detect the face, the size of the face, and the like. The facial expression identification unit 12 identifies facial expressions detected by the face detection unit 11.

  The face identification unit 13 generates face recognition data based on the facial feature points detected by the face detection unit 11 and stores the face recognition data in the memory 16. For example, the face identification unit 13 generates face recognition data from the positions of feature points such as eyes, nose, and mouth, and the relative distances between the feature points. Hereinafter, a person whose face recognition data is stored in the memory 16 is referred to as a registered person. Further, the face identifying unit 13 determines whether or not the person having the face detected by the face detecting unit 11 matches the registered person in the through image, the main image, and the image recorded on the recording medium 21. The subject extraction unit 14 extracts the main subject A from the main image and the image recorded on the recording medium 21 and determines the range of the background region B that does not include the main subject A.

  Further, the control unit 10 calculates a smile evaluation value indicating the degree of smile based on the smile evaluation reference table stored in advance in the memory 16. The smile evaluation value and the smile evaluation reference table will be described later. Further, the control unit 10 estimates the age and sex of the main subject A. Further, the control unit 10 calculates the luminance of the background region B.

  The display unit 15 displays various images under the control of the control unit 10. Various images displayed on the display unit 15 include a through image, a main image, an image recorded on the recording medium 21, a menu image, and the like. The operation unit 17 includes a release button 18 and a cross key 19. The release button 18 is operated by the user during imaging. The cross key 19 is operated on the above menu image or the like. The state of the release button 18 and the cross key 19 is detected by the control unit 10, and a sequence based on the detected button state is executed. The recording I / F unit 20 includes a connector for connecting the recording medium 21. When the recording I / F unit 20 and the recording medium 21 are connected, data writing / reading is executed on the recording medium 21. The bus 22 connects the buffer memory 5, the image processing unit 6, the control unit 10, the display unit 15, and the recording I / F unit 20, thereby executing data and signal input / output. The output of the A / D conversion unit 4 is connected to the image processing unit 6 via the bus 22.

  Here, the blurring process and the single color painting process in the image processing unit 6 will be described. First, the blurring process of the present embodiment is a process of expanding a bright spot using a point spreading function. FIG. 2 is a diagram illustrating the luminance distribution of the bright spots before and after the blurring process. The vertical axis in FIG. 2 indicates the luminance, and the horizontal axis indicates the spread from the luminance center.

  As shown in FIG. 2, the image processing unit 6 performs the blurring process so that the luminance information of the bright spots is the same before and after the blurring process. In FIG. 2, the luminance information is the area of the bright spot before the blurring process, that is, the area of the area E that is shaded, and the area of the bright spot after the blurring process, that is, the area F of the area F that is hatched. It corresponds to the area. The image processing unit 6 can obtain an image expressed so that the main subject A emerges by performing a blurring process on the background region B. In the present embodiment, the width dimension of the portion where the luminance is ½ of the peak is used as an index of the blurring degree. For example, the blurring degree in FIG.

  Further, the image processing unit 6 can change the way in which the bright spots are spread (hereinafter referred to as a blur shape). The blur shape has variations in the shape of a bright spot spread on a two-dimensional image and the attenuation of luminance from the center to the periphery. FIG. 3 is a diagram illustrating an example of a blurred shape. As shown in FIG. 3, the types of blur shapes include “Circle 1”, “Circle 2”, “Star”, etc., and the blur shape indicating “Circle 1” has a bright spot spread in a circular shape. In addition, the shape is blurred so that the outline of the bright spot becomes clear. Hereinafter, the blurred shape of “circle 1” will be described with reference numeral 31. The blur shape indicating “Circle 2” has a shape in which the bright spot portion spreads in a circular shape and the brightness decreases in a gradation shape from the center of the bright spot toward the radial direction. Hereinafter, the blurring shape of “circle 2” will be described with reference numeral 32. The blur shape indicating “star” is a shape in which the bright spot portion spreads in a star shape and is blurred so that the outline of the bright spot becomes clear. Hereinafter, the “star” blur shape will be described with reference numeral 33.

  An image in which the background region B of the main subject A is blurred differs depending on the situation of the main subject A and the background region B. For example, in the case of a bright shooting scene such as outdoors in the daytime on a sunny day, the main subject A appears more clearly using a blurring shape with an unclear outline such as the blurring shape 32 shown in “Circle 2”. It is possible to create a blurred image that is emphasized and has a little uncomfortable appearance. On the other hand, in the case of a dark scene such as a night view, the bright spot of the background region B is emphasized and more impressive when a blur shape with a clear outline such as the blur shape 31 shown in “Circle 1” is used. A blurred image can be created. In the case where the main subject A is an image of a child, if the blurring shape 33 shown by “star” is used, a fun and fairy tale effect can be produced, and the blurring process works effectively.

  The image processing unit 6 changes the blurring degree and the blurring shape by using different point spread functions. The same blurring process can be performed by using various digital filters such as a low-pass filter instead of the point spread function.

  Next, the single color painting process will be described. The image processing unit 6 changes the color information of all the pixels constituting the background region B to, for example, color information indicating black, blue, or green. As a result, an image in which the main subject A stands out. Further, the user can secondary use the main subject A using a computer or the like. For example, the user can perform a so-called chroma key composition in which the background region B after the monochrome filling process is replaced with another image.

  FIG. 4 is a flowchart showing the operation of the control unit 10 during imaging in the smile mode in the electronic still camera 1. Hereinafter, for the sake of convenience, description will be made on the premise of a scene in which one person is imaged.

  In step S101, the control unit 10 starts the smile mode. First, the control unit 10 receives a selection of processing to be performed on the main image from the user via the cross key 19. For example, the control unit 10 displays any menu image on the display unit 15, and any one of the blurring process, the monochrome painting process, and the process of generating a cutout image by cutting out a predetermined composition including the main subject A Accept a combination of Note that the selection of processing to be performed on the main image may be received after the main image is acquired (step S104). Hereinafter, an example in which a blurring process and a process of generating a cutout image are received will be described. Next, the control unit 10 controls the imaging device 3 to start acquiring a through image.

  In step S102, the face detection unit 11 detects a face from the through image. For example, the face detection unit 11 extracts a face by a feature point extraction process described in Japanese Patent Laid-Open No. 2001-16573. Examples of the feature points include eyebrow, eye, nose, and lip end points, face contour points, head apexes, and chin lower end points. Note that the face detection unit 11 can also detect a side face and an oblique face as disclosed in Japanese Patent Application Laid-Open No. 2007-94633.

  In step S103, the facial expression identification unit 12 determines whether the face detected in step S102 is a smile. For example, as shown in JP-A-8-249453 and JP-A-10-255043, the facial expression identification unit 12 has a total of six basic types of expressions such as anger, disgust, fear, sadness, smile, and surprise. Consider facial expressions, process time-series images from non-facial expressions to basic facial expressions, and identify facial expressions. When it is a smile (when determination of step S103 becomes YES), it progresses to step S104. On the other hand, when it is not a smile (when determination of step S103 becomes NO), it returns to step S102.

  In step S <b> 104, the control unit 10 controls the image sensor 3 to acquire a main image. Then, the control unit 10 controls the image processing unit 6 to perform image processing on the main image data and store it in the buffer memory 5. FIG. 5A shows an example of a main image in which a woman as the main subject A and a building as the background area B are captured.

  In step S105, the face detection unit 11 performs the same processing as in step S102, and detects the face of the main subject A from the main image.

  In step S106, the face detector 11 detects the size of the face of the main subject A. Then, the control unit 10 selects any one of a plurality of composition frames stored in advance in the memory 16 based on the size of the face of the main subject A. The control unit 10 may accept any one selection from a plurality of composition frames displayed on the display unit 15 via the cross key 19 from the user.

  Here, a composition frame 34 shown in FIG. 5B will be described as an example of the composition frame. As shown in FIG. 5 (2), the composition frame 34 includes a frame 35 indicating a face, a frame 36 indicating a general shape of the body, and a frame 37 indicating a cutout range. The aspect ratio of the composition frame 34 is the same as the aspect ratio of the main image. Hereinafter, an example in which the composition frame 34 is selected is shown.

  In step S107, the control unit 10 enlarges or reduces the composition frame 34 so that the size of the frame 35 indicating the face is the same as the size of the face of the main subject A. The enlarged or reduced composition frame 34 is defined as a composition frame 34 '. Then, the control unit 10 determines the position of the composition frame 34 ′ so that the frame 35 indicating the face matches the outline of the face of the main subject A. Thereafter, the control unit 10 displays the main image acquired in step S104 and the composition frame 34 'on the display unit 15 in an overlapping manner. An example in which the main image and the composition frame 34 'are displayed in an overlapping manner is shown in FIG. Thereby, the user can confirm the final composition.

  In step S108, the control unit 10 controls the image processing unit 6 to cut out the region 38 corresponding to the composition frame 34 'from the main image acquired in step S104. In the example of FIG. 5 (4), the shaded area is the area 38 corresponding to the composition frame 34 '.

  In step S109, the subject extraction unit 14 extracts the main subject A from the region 38 and determines the range of the background region B that does not include the main subject A in the following manner.

  First, the subject extraction unit 14 divides the region 38 into a plurality of regions by contour lines in the main image. For example, the subject extraction unit 14 divides the region 38 by edge extraction processing by the image processing unit 6. In this case, the image processing unit 6 performs edge extraction processing on the image data in the region 38 using a differential filter (such as a Laplacian filter). Then, the subject extraction unit 14 divides the region 38 into a plurality of regions based on the extracted contour line. Note that the subject extraction unit 14 may divide the region 38 into a plurality of regions by frequency component distribution analysis by discrete cosine transform in addition to edge extraction processing.

  Second, the subject extraction unit 14 determines the range of the main subject A and the background region B from the region 38 divided as described above, based on the face position of the main subject A.

  In step S110, the control unit 10 calculates a smile evaluation value of the main subject A. For example, as shown in Japanese Patent Application Laid-Open No. 2004-46591, the control unit 10 refers to the smile evaluation reference table, calculates the evaluation points of the shape of each element of the eyebrows, pupils, and lips of the face area, The smile evaluation value is calculated by adding the evaluation points weighted by a coefficient. The smile evaluation criterion table corresponds to an element area that stores data representing face components (for example, eyebrows, eyes, and lips) and a coefficient area that stores data representing coefficients of corresponding face components. A reference image of the constituent elements of the face to be operated and an evaluation point area for storing the evaluation points. The smile evaluation value is 100 points, and the closer to a full smile, the higher the score.

  In step S111, the control unit 10 estimates the age and sex of the main subject A using the inference process described in Japanese Patent Application Laid-Open No. 2007-280291. And the control part 10 determines with it being a child, when the age of the main subject A is below a threshold value.

  In step S112, the control unit 10 calculates the luminance of the background region B. For example, the control unit 10 calculates the luminance for each pixel for all the pixels constituting the background region B. Then, the control unit 10 divides the sum of the luminances by the number of pixels in the background region B, and calculates an average value of the luminances of all the pixels constituting the background region B.

  In step S113, the control unit 10 determines the blurring degree and the blurring shape by combining the following (a) to (e). Thereby, since the blurring process suitable for the smile of the main subject A can be performed, an image preferable as a portrait photograph can be obtained.

  (A) The control unit 10 increases the blurring degree as the smile evaluation value calculated in step S110 is higher. The relationship between the smile evaluation value and the blurring degree is shown in FIG. As a result, an image with a higher smile evaluation value and closer to a full smile has selected a brighter blur with a lower brightness at the center of the bright spot and a gentle attenuation from the center to the periphery, and the subject is more emphasized. It becomes an image. On the other hand, when the smile evaluation value is low, a weak blurring degree is selected, and the enhancement of the subject by the blurring process is suppressed.

  (B) The control unit 10 increases the degree of blurring as the luminance of the background region B calculated in step S112 is lower. FIG. 6B shows the relationship between the brightness of the background region B and the degree of blurring. Since an image with low brightness in the background region B does not stand out due to the blurring process, the strong blurring process can provide an image with a large effect of enhancing the main subject A and with a little uncomfortable feeling.

  (C) The control unit 10 increases the degree of blurring when it is estimated in step S111 that the main subject A is a child or a woman. This is because when the main subject A is an image of a child or a woman, an image that emphasizes the main subject A by strong blurring processing is preferred.

  (D) When the main subject A is a woman, the control unit 10 uses a blur shape 31 indicating “circle 1”, and when the main subject A is a child, the control unit 10 indicates a blur shape 33 indicating “star”. Is used. On the other hand, when the main subject A is an adult male, the blur shape 32 indicating “circle 2” is used. The relationship between the type of the main subject A and the blur shape is shown in FIG. When the main subject A is a woman, if the blurring shape 31 indicating “circle 1” is used, the bright spot of the background region B clearly spreads, and an impressive effect is obtained. In the case where the main subject A is a child, if the blur shape 33 indicating “star” is used, a fun and fairy tale effect can be produced and blur processing can be effectively performed. In addition, when the main subject A is a man, the production effects such as “Circle 1” and “Star” are often not suitable for the image of the man, but by using the blur shape 32 indicating “Circle 2”, An image in which the main subject A is emphasized without a sense of incongruity can be obtained.

  (E) When the smile evaluation value is 70 points or more, the control unit 10 uses the blurring shape 31 indicating “circle 1”, and when the smile evaluation value is less than 70 points, “circle 2”. A blur shape 32 indicating the above is used. The relationship between the smile evaluation value and the blurred shape is shown in FIG. When the smile evaluation value is high, the main subject A of the smile is more effectively enhanced by the blurring process in which the bright spot of the background region B is clearly expanded by the blur shape 31 indicating “circle 1”. . On the other hand, when the smile evaluation value is low, an image in which the main subject A is emphasized can be obtained while preventing the impression of an excessive effect by using the blurring shape 32 indicating “circle 2”.

  In step S114, the control unit 10 controls the image processing unit 6 to perform the blurring process on the background region B using the blurring degree and blurring shape determined in step S113 so that the main subject A emerges. Get the image expressed in. Then, the control unit 10 controls the image processing unit 6 to enlarge the image after the blurring process to the size of the main image. An example of the image after the blurring process and the enlargement is shown in FIG. In the example of FIG. 5 (5), since the main subject A is a woman, the blurring shape 31 indicating “circle 1” is used. Thereby, an impressive presentation effect can be given to the background region B, and femininity can be emphasized. Further, by using the composition frame 34, a suitable composition is obtained.

  In step S115, the control unit 10 records the image data subjected to the image processing in step S114 on the recording medium 21 as an image file, and ends a series of processing. In addition, it is preferable that the control unit 10 records the smile evaluation value, the blurring degree, and the blurring shape together with the image data in the image file as information such as a tag.

  Here, a procedure in which the face detection unit 11 identifies the main subject A in step S105 when the electronic still camera 1 of the first embodiment captures a scene including a plurality of persons will be described. For example, the face detection unit 11 automatically specifies the main subject A from a plurality of persons or specifies the main subject A from a plurality of persons based on a user instruction.

  For example, the face detection unit 11 automatically identifies the main subject A by any one of the following (1) to (3).

  (1) The control unit 10 calculates smile evaluation values for all the faces detected by the face detection unit 11. The face detection unit 11 sets the person with the highest smile evaluation value as the main subject A. This is because the person with the highest smile evaluation value is likely to be the main subject for the user.

  (2) The face detection unit 11 calculates the ratio of the face in the main image with respect to all detected faces. The face detection unit 11 sets a person whose ratio of the face in the main image is the maximum or a threshold (for example, 10%) or more as the main subject A. This is because a person whose face ratio is the maximum or greater than or equal to the threshold is likely to be a main subject for the user.

  (3) First, the face identification unit 13 determines whether or not all persons having the faces detected by the face detection unit 11 match the registered person. The determination as to whether or not the person matches the registered person is based on whether or not the face feature amount detected by the face detection unit 11 matches the face recognition data that is feature amount information stored in the memory 16 in advance. It is to judge. For example, the face identification unit 13 calculates the positions of the feature points such as the eyes, nose, and mouth of the face detected by the face detection unit 11 and the relative distances between the feature points. Next, the face identification unit 13 compares the calculation result with the registered person's face recognition data stored in the memory 16, and compares the registered person's face with the face detected by the face detection unit 11. Find similarity. Then, the face identification unit 13 determines that the person having the face detected by the face detection unit 11 matches the registered person when the similarity is greater than the threshold value.

  Thereafter, the face detection unit 11 sets a person determined to match the registered person as the main subject A. This is because a person who is determined not to match the registered person (hereinafter referred to as an unregistered person) is likely to be a passing person or an unknown person. The control unit 10 may display a message such as “A person other than the main character has been detected” on the display unit 15 when there is a non-registered person.

  Next, when specifying the main subject A based on the user's instruction, the control unit 10 accepts selection of the main subject A via the touch panel provided on the display unit 15. The main subject A may be a plurality of persons. Further, the selection of the main subject A may be received via the cross key 19 without being limited to the touch panel. When selection of a plurality of persons is accepted as the main subject A, the control unit 10 selects a composition frame based on the number and size of the faces or smiles of the main subject A in step S106.

  As described above, the electronic still camera 1 of the first embodiment extracts a person who becomes a smile from the main image as the main subject A, and performs a blurring process on the background region B, a single color painting process, or a predetermined target including the main subject A. The process which produces | generates the cutout image of this composition is performed. Therefore, according to the electronic still camera 1 of the first embodiment, a passing person or an unknown person included in the background area B is conspicuous, thereby eliminating the possibility that the smile of the main subject A will be spoiled. Therefore, it is possible to obtain a preferable image in terms of composition or picture.

  Further, since the electronic still camera 1 of the first embodiment identifies a smile and automatically acquires a main image, it is possible to eliminate the possibility of missing a photo opportunity.

  In the first embodiment, an example is shown in which the main image is automatically acquired when a smile is identified by the facial expression identification unit 12 in the smile mode, but the present invention is not limited to this. For example, when a sadness or anger expression is recognized, such as a sadness mode or an anger mode, a function of automatically acquiring the main image may be used. Even if these functions are in operation, it is desirable that the main image can be obtained at any time if the user fully presses the release button 18. Further, in the shooting mode, the processing after step S105 in FIG. 4 may be performed on the main image acquired by fully pressing the release button 18.

  In the first embodiment, the example in which the blurring process is performed on the main image acquired at the time of imaging is shown, but the present invention is not limited to this. For example, the same image processing may be performed on an image recorded on the recording medium 21 during reproduction.

  In the first embodiment, the example in which the background region B is subjected to the blurring process after the region 38 corresponding to the composition frame 34 ′ is cut out from the main image has been described. However, the present invention is not limited to this. For example, after detecting the face of the main subject A from the main image in step S105, the processing from step S109 to step S114 may be performed, and then the processing from step S106 to step S108 may be performed.

  Further, in the first embodiment, an example of performing the blurring process and the process of generating the cut-out image has been described. However, when the single color filling process is selected in step S101, the subject extraction unit 14 performs the process after step S105. The main subject A is extracted, and the range of the background region B that does not include the main subject A is determined. Thereafter, the control unit 10 may control the image processing unit 6 to change the color information of all the pixels constituting the background region B to predetermined color information.

(Second Embodiment)
Hereinafter, a second embodiment of the present invention will be described. In the first embodiment, in the smile mode, the example in which the main image is automatically acquired when the face detected in the through image is identified as a smile has been described. However, in the second embodiment, the through image is automatically acquired. An example will be shown in which whether or not there is a non-registered person in the image is taken into account as an acquisition condition for the main image. For example, in the electronic still camera 1 of the second embodiment, only when the non-registered person does not exist in the through image, the “smile mode 1” in which the smile image of the registered person is acquired as the main image; The “smile mode 2” that allows a smile image of a registered person to be acquired as a main image even if it exists in the image. The control unit 10 can accept a selection of “smile mode 1” or “smile mode 2” from the user via the cross key 19 in advance. Note that the electronic still camera 1 according to the second embodiment may be configured such that the main image can be acquired at any time if the user fully presses the release button 18 even when these modes are in operation. desirable. Here, the configuration of the electronic still camera in the following embodiment is common to the electronic still camera 1 of the first embodiment shown in FIG.

  FIG. 7 is a flowchart illustrating the operation of the control unit 10 during imaging in “smile mode 1” in the electronic still camera 1 according to the second embodiment.

  In step S201, the control unit 10 starts “smile mode 1”. First, the control unit 10 performs the same processing as that in step S101 in FIG. 4 and receives selection of processing to be performed on the main image from the user via the cross key 19. Next, the control unit 10 controls the imaging device 3 to start acquiring a through image.

  In step S202, the face detection unit 11 performs processing similar to that in step S102 in FIG. 4 to detect a face from the through image.

  In step S203, the face identification unit 13 determines whether or not a registered person exists among the persons having the face detected in step S202. An example in which registered persons 51 and 52 and non-registered persons 53 exist in the through image is shown in FIG. As shown in FIG. 9A, the frame indicating the face of the non-registered person 53 and the frame indicating the face of the registered persons 51 and 52 may be displayed differently. When there is a registered person (when the determination in step S203 is YES), the process proceeds to step S204. On the other hand, when there is no registered person (when determination of step S203 becomes NO), it returns to step S202.

  In step S204, the face identification unit 13 determines whether or not a non-registered person exists among the persons having the face detected in step S202. If there is no unregistered person (when the determination in step S204 is NO), the process proceeds to step S206. On the other hand, when there is a non-registered person (when the determination in step S204 is YES), after displaying a warning message in step S205, the process returns to step S202.

  Here, in step S205, for example, the control unit 10 displays a message such as “A person other than the main character has been detected” on the display unit 15, as shown in FIG. As a result, the user can see that a passing person or an unknown person appears in the through image.

  In step S206, the facial expression identification unit 12 performs the same process as in step S103 of FIG. 4, and determines whether or not the person determined to be a registered person in step S203 is a smile. When it is a smile (when determination of step S206 becomes YES), it progresses to step S207. On the other hand, when it is not a smile (when determination of step S206 becomes NO), it returns to step S202.

  In step S207, the control unit 10 controls the image sensor 3 to acquire the main image. Then, the control unit 10 controls the image processing unit 6 to perform image processing on the main image data and store it in the buffer memory 5.

  In step S208, the control unit 10 controls the image processing unit 6 to perform a blurring process, a single color painting process, or a predetermined subject including the main subject A on the background region B of the main image according to the process accepted in step S201. Processing for generating a cut-out image of the composition is performed. At this time, a person matching the registered person is extracted as the main subject A. When a process for generating a cut-out image is received, the control unit 10 selects a composition frame based on the number and size of the faces or smiles of the main subject A. Note that the process of step S208 is not necessarily performed, and the recording may be performed directly on the recording medium in step S209.

  In step S209, the control unit 10 records the main image data subjected to various processes in step S208 as an image file on the recording medium 21, and ends the series of processes. In addition, it is preferable that the control unit 10 records the smile evaluation value, the blurring degree, and the blurring shape together with the image data in the image file as information such as a tag.

  Next, “smile mode 2” will be described. FIG. 8 is a flowchart illustrating the operation of the control unit 10 during imaging in the “smile mode 2” in the electronic still camera 1 according to the second embodiment.

  In step S301, the control unit 10 starts “smile mode 2”. First, the control unit 10 performs a process similar to that in step S201 in FIG. 7 and receives a selection of a process to be performed on the main image from the user via the cross key 19. Next, the control unit 10 controls the imaging device 3 to start acquiring a through image.

  In step S302, the face detection unit 11 performs processing similar to that in step S202 in FIG. 7, and detects a face from the through image.

  In step S303, the face identification unit 13 determines whether or not a registered person exists among the persons having the face detected in step S302. When there is a registered person (when the determination in step S303 is YES), the process proceeds to step S304. On the other hand, when there is no registered person (when the determination in step S303 is NO), the process returns to step S302.

  In step S304, the face identification unit 13 determines whether or not a non-registered person exists among the persons having the face detected in step S302. If there is an unregistered person (when the determination in step S304 is YES), the process proceeds to step S306 after displaying a warning message in step S305. On the other hand, when there is no unregistered person (when the determination in step S304 is NO), the process proceeds to step S307.

  Here, in step S305, for example, the control unit 10 displays a message such as “A person other than the main character has been detected” on the display unit 15, as shown in FIG. As a result, the user can see that a passing person or an unknown person appears in the through image.

  In step S306, it is determined whether or not the main image is to be acquired even if a non-registered person exists. The determination is performed by the user setting in advance on a smile mode setting screen as shown in FIG. 10, for example. If the main image is acquired even when there is an unregistered person (when the determination in step S306 is YES), the process proceeds to step S307. On the other hand, if there is an unregistered person and the main image is not acquired (when the determination in step S306 is NO), the process returns to step S302.

  In step S307, the facial expression identification unit 12 performs the same process as in step S206 in FIG. 7, and determines whether or not the person determined to be a registered person in step S303 is a smile. If it is a smile (if the determination in step S307 is YES), the process proceeds to step S308. On the other hand, when it is not a smile (when determination of step S307 becomes NO), it returns to step S302.

  In step S308, the control unit 10 calculates a smile evaluation value of the person determined to be a registered person in step S303. When the smile evaluation value is equal to or greater than a threshold value (for example, 80 points) (when the determination in step S308 is YES), the process proceeds to step S309. On the other hand, when the smile evaluation value is less than the threshold value (when the determination in step S308 is NO), the process returns to step S302.

  Steps S309 to S311 correspond to steps S207 to S209 in FIG. Further, similarly to FIG. 7, the processing as in S310 is not necessarily performed, and the recording may be performed on the recording medium in S311 as it is. Note that the control unit 10 may display on the display unit 15 that image processing is in progress, as shown in FIG.

  In “smile mode 2”, whether or not to acquire the main image is determined according to the smile evaluation value of the registered person, but the present invention is not limited to this. For example, the depth of field may be used to determine whether to acquire the main image. In this case, in step S308 in FIG. 8, the control unit 10 determines whether or not the unregistered person is out of the depth of field. In step S309, the control unit 10 may acquire the main image when it is determined that the non-registered person is out of the depth of field. In this case, since the non-registered person is blurred, the risk of ruining the smile of the registered person can be reduced. Whether or not it is out of the depth of field can be determined by analyzing the sharpness of the image, that is, the degree of blur of the image. For example, the control unit 10 controls the image processing unit 6 to perform edge extraction processing on the through image data. Then, the control unit 10 may analyze the degree of blur of the image based on the extracted edge amount. When a plurality of lenses are used as the imaging optical system, the depth of field changes depending on the shooting magnification. Therefore, the control unit 10 may determine whether or not a non-registered person is out of the depth of field based on the changing depth of field.

  As described above, the electronic still camera 1 according to the second embodiment has a configuration in which whether or not a non-registered person exists in the through image is taken into consideration as the acquisition condition of the main image. According to smile mode 1, since a smile image of a registered person is acquired as a main image only when a non-registered person does not exist in the through image, interruptions by persons other than the main subject A (registered person) are surely avoided. It is possible to obtain an image that is preferable in terms of composition or picture. Also, according to “smile mode 2”, even if a non-registered person exists in the through image, it is possible to acquire the smile image of the registered person as the main image, so an image that is preferable in terms of composition or picture is acquired. This is possible, and the photo opportunity can be increased as compared with the “smile mode 1”. Further, in the electronic still camera 1 according to the second embodiment, even when these modes are in operation, if the user fully presses the release button 18, the configuration can be obtained at any time. , You won't miss a photo opportunity, making it a more convenient camera.

  Note that a smile evaluation value serving as a threshold value may be received from the user via the cross key 19 in step S304.

Moreover, in 2nd Embodiment, after performing the process of step S203 and step S204, the process of step S206 is performed, However, it is not restricted to this. For example, the processing in step S203 and step S204 may be performed after the processing in step S206.
(Supplement of embodiment)
(1) In the first embodiment and the second embodiment, the example of the electronic still camera has been described, but the present invention is not limited to this. For example, the program installed in the computer can be provided with the functions shown in the procedure for performing the blurring process, the procedure for performing the single color painting process, and the procedure for generating the cut-out image in the first and second embodiments. In this case, it is possible to store the image processing program in a storage medium in advance and execute or install the image processing program after connecting to the computer.

  (2) In the first embodiment and the second embodiment, three types of blur shapes are shown: a blur shape 31 indicating “circle 1”, a blur shape 32 indicating “circle 2”, and a blur shape 33 indicating “star”. However, it is not limited to this. For example, a blur shape indicating “heart” may be used. The blurring shape indicating the “heart” has a shape in which the bright spot portion spreads in a heart shape and is blurred so that the outline of the bright spot becomes clear.

  (3) In the first embodiment and the second embodiment, the example in which the above (a) to (e) are combined as elements for determining the blurring degree and the blurring shape has been described, but the blurring degree and the blurring shape are determined. The element is not limited to this.

  (4) In the electronic still camera 1 of the first embodiment and the second embodiment, when capturing a scene including a plurality of persons such as a group photo, the main image can be acquired with priority given to the smile of the registered person. A function of “registered person priority” may be provided.

  (5) In the smile mode of the first embodiment and the second embodiment, a configuration may be adopted in which a smile evaluation value serving as a reference for acquiring the main image can be set for each registered person. As a result, for example, a person who does not usually laugh very much can set to automatically acquire the main image by identifying it as a smile even if he laughs a little.

DESCRIPTION OF SYMBOLS 1 ... Electronic still camera, 2 ... Image sensor, 6 ... Image processing part, 7 ... Compression / decompression processing part, 10 ... Control part, 15 ... Display part, 17 ... Operation part

JP 2008-042319 A

Claims (13)

A face detection unit for detecting a face from a captured through image;
A facial expression identification unit that identifies facial expressions detected by the face detection unit;
An imaging unit for acquiring a main image when the facial expression identification unit identifies that the facial expression is a smile;
A subject extraction unit that extracts a subject that smiles from the main image as a main subject;
An image processing unit that performs processing to blur the area other than the main subject on the main image ;
An evaluation value calculation unit for calculating a smile evaluation value indicating the degree of smile of the main subject;
With
The electronic still camera , wherein the image processing unit determines at least one of a blurring shape and a blurring degree used for blurring processing according to the smile evaluation value . The electronic still camera according to claim 1.
The subject extraction unit extracts, as the main subject, a subject having the highest smile evaluation value calculated by the evaluation value calculation unit when a plurality of subjects to be smiling are extracted from the main image. An electronic still camera. A face detection unit for detecting a face from a captured through image;
A facial expression identification unit that identifies facial expressions detected by the face detection unit;
An imaging unit for acquiring a main image when the facial expression identification unit identifies that the facial expression is a smile;
A subject extraction unit that extracts a subject that smiles from the main image as a main subject;
An image processing unit that performs processing to blur the area other than the main subject on the main image;
A luminance calculation unit for calculating luminance of an area other than the main subject;
With
The electronic still camera , wherein the image processing unit determines at least one of a blurring shape and a blurring degree used for blurring processing according to the luminance calculated by the luminance calculation unit . A face detection unit for detecting a face from a captured through image;
A facial expression identification unit that identifies facial expressions detected by the face detection unit;
An imaging unit for acquiring a main image when the facial expression identification unit identifies that the facial expression is a smile;
A subject extraction unit that extracts a subject that smiles from the main image as a main subject;
An image processing unit that performs processing to blur the area other than the main subject on the main image;
An estimation unit for estimating at least one of the age and sex of the main subject;
With
The electronic still camera , wherein the image processing unit determines at least one of a blurring shape and a blurring degree used for blurring processing according to an estimation result by the estimation unit . In the electronic still camera according to claim 3 or 4 ,
An evaluation value calculation unit for calculating a smile evaluation value indicating the degree of smile;
The subject extraction unit extracts, as the main subject, a subject having the highest smile evaluation value calculated by the evaluation value calculation unit when a plurality of subjects to be smiling are extracted from the main image. An electronic still camera. In the electronic still camera according to claim 3 or 4 ,
A ratio calculator that calculates a ratio of the smile area in the main image;
The subject extraction unit extracts, as the main subject, a subject having the highest ratio of the smile area in the main image when a plurality of subjects that are smiling are extracted from the main image. Electronic still camera. The electronic still camera according to any one of claims 1 to 6 ,
A storage unit for storing feature amount information indicating a feature amount of a face;
A face identifying unit that determines whether or not the extracted feature amount and the feature amount information match after extracting the facial feature amount detected by the face detection unit ;
The imaging unit acquires the main image when it is determined that the feature quantity of the face detected by the face identification unit matches the feature quantity information stored in the storage unit, and the feature quantity is acquired. The electronic still camera is characterized in that the acquisition of the main image is prohibited when a face determined to not match the feature amount information is included . The electronic still camera according to any one of claims 1 to 6 ,
A storage unit for storing feature amount information indicating a feature amount of a face;
A face identifying unit that determines whether or not the extracted feature amount and the feature amount information match after extracting the facial feature amount detected by the face detection unit;
In a case where a face for which the feature amount detected by the face identification unit is determined not to match the feature amount information stored in the storage unit is included, the imaging unit acquires the main image It is possible to select whether or not to perform the electronic still camera. The electronic still camera according to claim 8 .
When the imaging unit selects to acquire the main image, the imaging unit acquires the main image when a smile evaluation value of a face determined to match the feature amount and the feature amount information is equal to or greater than a threshold value. An electronic still camera characterized by The electronic still camera according to any one of claims 1 to 6 ,
A storage unit for storing feature amount information indicating a feature amount of a face;
A face identifying unit that determines whether or not the extracted feature amount and the feature amount information match after extracting the feature amount of the face detected by the face detection unit;
A sharpness determination unit that determines whether or not the face detected from the through image is blurred,
If the face that has been determined that the feature quantity detected by the face identification unit does not match the feature quantity information stored in the storage unit is included, and the face is blurred The electronic still camera is characterized in that the unit can select whether or not to acquire the main image . The electronic still camera according to any one of claims 1 to 6,
  A storage unit for storing feature amount information indicating a feature amount of a face;
  A face identifying unit that determines whether or not the extracted feature amount and the feature amount information match after extracting the facial feature amount detected by the face detection unit;
  Acquisition of the main image by the imaging unit when a face determined by the face identification unit that the feature amount detected by the face and the feature amount information stored in the storage unit do not match is included And a second mode for selecting whether or not to acquire the main image.
  This is an electronic still camera. A face detection unit for detecting a face from a captured through image;
  A facial expression identification unit that identifies facial expressions detected by the face detection unit;
  An imaging unit for acquiring a main image when the facial expression identification unit identifies that the facial expression is a smile;
  A subject extraction unit that extracts a subject that smiles from the main image as a main subject;
  A process of blurring an area other than the main subject on the main image, a process of painting an area other than the main object on the main image in a single color, or a predetermined composition including the main object in the main image. In addition to the image processing unit that performs at least one of the processes for generating a cutout image by cutting out,
  A storage unit for storing feature amount information indicating a feature amount of a face;
  A face identifying unit that determines whether or not the extracted feature amount and the feature amount information match after extracting the facial feature amount detected by the face detection unit;
  The subject extraction unit extracts, as a main subject, a subject having a feature amount that matches the feature amount information by the face identification unit when a plurality of subjects to be smiled are extracted from the main image.
  This is an electronic still camera. A face detection unit for detecting a face from a captured through image;
  A facial expression identification unit that identifies facial expressions detected by the face detection unit;
  An imaging unit for acquiring a main image when the facial expression identification unit identifies that the facial expression is a smile;
  A subject extraction unit that extracts a subject that smiles from the main image as a main subject;
  A process of blurring an area other than the main subject on the main image, a process of painting an area other than the main object on the main image in a single color, or a predetermined composition including the main object in the main image. In addition to the image processing unit that performs at least one of the processes for generating a cutout image by cutting out,
  A storage unit for storing feature amount information indicating a feature amount of a face;
  A face identifying unit that determines whether or not the extracted feature amount and the feature amount information match after extracting the feature amount of the face detected by the face detection unit;
  A sharpness determination unit that determines whether or not the face detected from the through image is blurred,
  If the face that has been determined that the feature quantity detected by the face identification unit does not match the feature quantity information stored in the storage unit is included, and the face is blurred Can select whether or not to acquire the main image
  This is an electronic still camera.

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