WO2020001016A1

WO2020001016A1 - Moving image generation method and apparatus, and electronic device and computer-readable storage medium

Info

Publication number: WO2020001016A1
Application number: PCT/CN2019/073077
Authority: WO
Inventors: 李旭刚; 冯宇飞; 柳杨光
Original assignee: 北京微播视界科技有限公司
Priority date: 2018-06-29
Filing date: 2019-01-25
Publication date: 2020-01-02
Also published as: CN108961314B; CN108961314A

Abstract

A moving image generation method and apparatus, and an electronic device and a computer-readable storage medium. The moving image generation method comprises: detecting a target object using an image sensor (S101); identifying an outer frame of the target object (S102); using one or more side lengths of the outer frame to calculate a distance coefficient between the target object and the image sensor (S103); and using the distance coefficient to generate a moving image of the target object (S104). The problem of a jumping phenomenon occurring when the image area is used to determine a movement trajectory of a target object in the prior art is solved, thereby making a moving image smoother.

Description

Moving image generating method, device, electronic device and computer-readable storage medium

cross reference

This disclosure refers to a Chinese patent application with the application number 201810699053.5, which is filed on June 29, 2018 and is entitled "Motion image generation method, device, electronic device, and computer-readable storage medium", which is incorporated by reference in its entirety Application.

Technical field

The present disclosure relates to the field of image processing, and in particular, to a method, a device, an electronic device, and a computer-readable storage medium for generating a moving image.

Background technique

With the development of computer technology, the application range of smart terminals has been widely improved, such as listening to music, playing games, chatting on the Internet, and taking photos through the smart terminal. For the smart terminal's camera technology, the camera pixels have reached more than 10 million pixels, which has higher resolution and is comparable to that of professional cameras.

Current mobile terminals can identify and collect user actions and form moving images.

Summary of the invention

However, the inventor has found through research that at present, when recording the motion trajectory of an object, the method of calculating the trajectory of a certain characteristic of the object is generally used. Generally, the contour range can be expressed by a polygon or a circle. The distance of an object can be expressed by the area of a polygon. The larger the area, the closer it is, and the smaller the area, the farther it is. However, when recording the motion of an object, Because the area will change, it will cause the motion trajectory or speed of the object to change, making the image look uneven.

Therefore, if a method for generating a moving image can be provided so that the moving trajectory and the moving speed of an object in the image do not change suddenly, the shooting effect of the image and the user experience can be greatly improved.

In view of this, an embodiment of the present disclosure provides a method for generating a moving image, which is used to smooth a moving trajectory or a moving speed of an object in the image so that the image looks smoother.

In a first aspect, an embodiment of the present disclosure provides a method for generating a moving image, including: using an image sensor to detect a target object; identifying an outer frame of the target object; using one or more sides of the outer frame to calculate the target object and A distance coefficient between image sensors; using the distance coefficient to generate a moving image of the target object.

Optionally, the step of calculating the distance coefficient includes: calculating a current distance coefficient between the target object and the image sensor using one or more side lengths of the outer frame, and calculating a distance coefficient using the current distance coefficient and the historical distance coefficient.

Optionally, the historical distance coefficient is one of the following: the distance coefficient between the target object and the image sensor in the previous image frame; the distance coefficient between the target object and the image sensor at the last moment; and the current The average of multiple distance coefficients between the target object and the image sensor in multiple times or multiple frames of images before the time.

Optionally, the calculating the distance coefficient using the current distance coefficient and the historical distance coefficient includes: multiplying the current distance coefficient by a first weight coefficient to obtain a first weight distance coefficient; multiplying the historical distance coefficient by a second weight coefficient to obtain a second Weighted distance coefficient; add the first weighted distance coefficient and the second weighted distance coefficient to obtain the distance coefficient.

Optionally, the generating a moving image of the target object using the distance coefficient includes generating a moving image of the target object using multiple distance coefficients.

Optionally, the target object is a palm, and the outer frame is a smallest rectangle covering the palm.

Optionally, the length of the long side of the rectangle is L, the length of the wide side is W, and the distance coefficient is:

f (x) = Ax ^a

Where x = L + W, A is a real number greater than 0, and 0 <a <1.

Optionally, calculate the distance coefficient using the current distance coefficient and the historical distance coefficient, including:

f '(x) = αf ( x n) + βf (x n-1)

Where α> 0, β> 0, and α + β = 1, n≥2; f ′ (x) represents the distance coefficient, f (x _n ) represents the current distance coefficient, and f (x _n-1 ) represents the previous moment Distance factor.

Optionally, detecting the target object using the image sensor includes: obtaining color information of the image and position information of the color information using the image sensor; comparing the color information with preset palm color information; identifying the first color information, The error between the first color information and the preset palm color information is less than a first threshold; and the position information of the first color information is used to form a contour of the palm.

In a second aspect, an embodiment of the present disclosure provides a moving image generating device including: a detection module for detecting a target object using an image sensor; a recognition module for identifying an outer frame of the target object; a distance coefficient calculation module for A distance coefficient between the target object and the image sensor is calculated by using one or more side lengths of the outer frame; an image generating module is configured to use the distance coefficient to generate a moving image of the target object.

Optionally, the distance coefficient calculation module includes: a first distance coefficient calculation module for calculating a current distance coefficient between the target object and the image sensor by using one or more side lengths of the outer frame; a second distance coefficient The calculation module is configured to calculate the distance coefficient by using the current distance coefficient and the historical distance coefficient.

Optionally, the second distance coefficient calculation module includes: a first weighted distance coefficient calculation module, configured to multiply the current distance coefficient by the first weighted coefficient to obtain a first weighted distance coefficient; a second weighted distance coefficient calculation module, The second distance coefficient is obtained by multiplying the historical distance coefficient by the second weight coefficient. The third distance coefficient calculation module is configured to add the first weight distance coefficient and the second weight distance coefficient to obtain the distance coefficient.

Optionally, the image generating module is configured to generate a moving image of the target object using multiple distance coefficients.

f (x) = Ax ^a

Where x = L + W, A is a real number greater than 0, and 0 <a <1.

f '(x) = αf ( x n) + βf (x n-1)

Optionally, the detection module includes: an information acquisition module for acquiring color information of the image and position information of the color information using an image sensor; a comparison module for comparing the color information with preset palm color information; A recognition module, configured to recognize first color information, and an error between the first color information and the preset palm color information is less than a first threshold; a contour forming module, configured to form position information using the first color information Palm silhouette.

According to a third aspect, an embodiment of the present disclosure provides an electronic device, including:

At least one processor; and

A memory connected in communication with the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can perform any one of the foregoing movements of the first aspect Image generation method.

According to a fourth aspect, an embodiment of the present disclosure provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute any one of the foregoing first aspects. The moving image generating method.

Embodiments of the present disclosure provide a method, an apparatus, an electronic device, and a computer-readable storage medium for generating a moving image. The moving image generating method includes: detecting a target object using an image sensor; identifying an outer frame of the target object; using one or more side lengths of the outer frame to calculate a distance coefficient between the target object and the image sensor; The distance coefficient generates a moving image of the target object. By adopting this technical solution, the embodiment of the present disclosure solves the jump phenomenon in determining the motion trajectory of the target object using the image area in the prior art, and makes the moving image smoother.

The above description is only an overview of the technical solutions of the present disclosure. In order to better understand the technical means of the present disclosure, it can be implemented in accordance with the contents of the description, and in order to make the above and other objects, features, and advantages of the present disclosure more understandable The following describes the preferred embodiments in detail with reference to the drawings, as follows.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to explain the technical solutions in the embodiments of the present disclosure or the prior art more clearly, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description These are some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without paying creative labor.

FIG. 1 is a flowchart of Embodiment 1 of a moving image generating method according to an embodiment of the present disclosure;

2 is a flowchart of a second embodiment of a moving image generating method according to an embodiment of the present disclosure;

3 is a flowchart of a third embodiment of a moving image generating method according to an embodiment of the present disclosure;

4 is a schematic structural diagram of Embodiments 1, 2, and 3 of a moving image generating device according to an embodiment of the present disclosure;

5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

6 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present disclosure;

FIG. 7 is a schematic structural diagram of a moving image generating terminal according to an embodiment of the present disclosure.

detailed description

The following describes the implementation of the present disclosure through specific specific examples. Those skilled in the art can easily understand other advantages and effects of the present disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, but not all the embodiments. The present disclosure can also be implemented or applied through other different specific implementations, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present disclosure.

It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, those skilled in the art should understand that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, any number of the aspects set forth herein may be used to implement a device and / or a practice method. In addition, the apparatus and / or the method may be implemented using other structures and / or functionality in addition to one or more of the aspects set forth herein.

It should also be noted that the illustrations provided in the following embodiments only illustrate the basic idea of the present disclosure in a schematic manner, and the drawings only show components related to the present disclosure and not the number, shape, For size drawing, the type, quantity, and proportion of each component can be changed at will in actual implementation, and the component layout type may be more complicated.

In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects may be practiced without these specific details.

FIG. 1 is a flowchart of Embodiment 1 of a moving image generating method according to an embodiment of the present disclosure. The moving image generating method provided in this embodiment may be executed by a moving image generating device, and the moving image generating device may be implemented as software. Or implemented as a combination of software and hardware, the moving image generating device may be integrated in a certain device in the image processing system, such as an image processing server or an image processing terminal device. The core idea of this embodiment is: use the side length of the outer frame of the target object to indicate the distance between the target object and the image sensor, and use this distance to generate a moving image of the target object.

As shown in Figure 1, the method includes the following steps:

S101. Use an image sensor to detect a target object.

In this embodiment, the target object may be any object that can be recognized by the image sensor, such as a tree, an animal, a person, or a part of the entire object, such as a human face, a human hand, and the like.

Detecting a target object includes locating feature points of the target object and identifying the target object. Feature points are points in the image that have distinct characteristics and can effectively reflect the essential characteristics of the image and can identify the target object in the image. If the target object is a human face, then the key points of the face need to be obtained. If the target image is a house, then the key points of the house need to be obtained. Take the human face as an example to illustrate the acquisition of key points. The face contour mainly includes 5 parts: eyebrows, eyes, nose, mouth and cheeks, and sometimes also includes pupils and nostrils. Generally speaking, a complete description of the face contour is achieved. The number of key points required is about 60. If only the basic structure is described, the details of each part do not need to be described in detail, or the cheeks need not be described, then the number of key points can be reduced accordingly. If you need to describe the pupils, nostrils, or need More detailed features can increase the number of key points. Face keypoint extraction on the image is equivalent to finding the corresponding position coordinates of each face contour keypoint in the face image, that is, keypoint positioning. This process needs to be performed based on the characteristics of the keypoint corresponding. After clearly identifying the image features of the key points, a search and comparison is performed in the image based on this feature to accurately locate the positions of the key points on the image. Because the feature points occupy only a very small area in the image (usually only a few to tens of pixels in size), the area occupied by the features corresponding to the feature points on the image is also usually very limited and local. The features currently used There are two ways of extraction: (1) one-dimensional range image feature extraction along the vertical contour; (2) two-dimensional range image feature extraction of square neighborhood of feature points. There are many ways to implement the above two methods, such as ASM and AAM methods, statistical energy function methods, regression analysis methods, deep learning methods, classifier methods, batch extraction methods, and so on. The number of key points, accuracy, and speed used by the above various implementation methods are different, which are suitable for different application scenarios. Similarly, for other target objects, the same principle can be used to identify target objects.

In this embodiment, the position where the target object exists is found from the image collected by the image sensor and the target object is segmented from the background. Here, the position where the target object exists can be located using color, and the target object is determined by color. Rough matching; feature extraction and recognition of target object images found and segmented.

S102. Identify the outer frame of the target object.

After the target object is detected, a polygon is delineated outside the outer contour of the target object. In this embodiment, the polygon is actually any shape such as a circle, but it is preferable to easily calculate the area or the side length or perimeter. For the shape, a rectangle is taken as an example. After the feature points of the target object are identified, the width at the widest point and the length at the longest point of the target object can be calculated, and the rectangle of the outer border of the target object can be identified with the width and length. An implementation of calculating the longest and widest points of the target object is to extract the boundary feature points of the target object, calculate the difference between the X coordinates of the two boundary feature points with the furthest X coordinate distances, and calculate Y as the width of the rectangle. The difference between the Y coordinates of the two boundary feature points with the furthest coordinate distance is taken as the length of the rectangle. If the target object is a fist, the outer frame may be set to the smallest circle covering the fist, so that the side length of the outer frame may be the radius or perimeter of the circle.

S103. Calculate a distance coefficient between the target object and the image sensor by using one or more sides of the outer frame.

S104. Use the distance coefficient to generate a moving image of the target object.

In this embodiment, the distance coefficient between the target object and the image sensor is calculated using one or more sides of the outer frame, and the distance coefficient indicates the distance between the target object and the image sensor. Specifically, when the outer frame is rectangular, the wide or long sides of the rectangle may be used to calculate the distance coefficient between the target object and the image sensor, or the sum of the wide and long sides of the rectangle may be used to calculate Because the distance coefficient is linear, the distance coefficient is calculated linearly, and no jump occurs. The side length or the sum of the side lengths of the outer frame can directly represent the distance between the target object and the image sensor, and can also participate in the calculation of the distance as a distance coefficient, that is, the distance and the side length of the outer frame are constant. The function relationship is specifically what kind of function relationship is satisfied. The user can customize or use the function preset in the system. Each function relationship can present different moving image effects.

In the technical solution in the foregoing embodiment, the distance coefficient between the target object and the image sensor is calculated based on identifying the outer frame of the target object based on the side length of the outer frame. Because the edge length of the outer frame changes linearly with distance, it can better reflect the motion trajectory of the object, avoiding the jump caused by using the outer frame area to indicate the distance in the prior art, and making the image jump.

FIG. 2 is a flowchart of a second embodiment of a moving image generating method according to an embodiment of the present disclosure. As shown in FIG. 2, the method may include the following steps:

S201: Use an image sensor to detect a target object;

S202. Identify the outer frame of the target object.

S203. Calculate a current distance coefficient between the target object and the image sensor by using one or more side lengths of the outer frame, and calculate a distance coefficient by using the current distance coefficient and the historical distance coefficient.

S204. Use the distance coefficient to generate a moving image of the target object.

In this embodiment, in order to make the motion of the image smoother, a historical distance coefficient is added, and the historical distance coefficient is added to the current distance coefficient to calculate the actual distance coefficient to be used. To this end, the system needs to set a cache to cache at least one historical distance coefficient, that is, after the distance coefficient is calculated, it is immediately sent to the corresponding cache for future distance coefficient calculation.

In an implementation manner, the historical distance coefficient is a distance coefficient between a target object and an image sensor in a previous image frame, and a distance calculation frequency is calculated once for each frame of the image; or the historical distance coefficient is a target at a previous moment The distance coefficient between the object and the image sensor. The last time can be the last calculated time or a user-defined time, such as 1 second. This time should be set before the method runs to tell Which distance coefficients the system needs to save; or the historical distance coefficient is the average of multiple distance coefficients before the current time. The calculation of the average value may be an absolute bisection of the values, or an average value with weights. Here is an implementation method of the average value with weights. If there are 5 historical distance coefficients, these 5 historical distances The coefficients are sorted by time to form a historical distance coefficient vector.

Sets the smoothing matrix, which is a vector of time weight coefficients

Then

with

The convolution calculation is performed to obtain the average value of multiple distance coefficients. Among the average values, 5 historical distance coefficients have a greater weight as the distance coefficients closer to the current time, so that the calculated historical distance coefficients are smoother and Closer to the true historical distance coefficient.

In an implementation manner, the calculating the distance coefficient by using the current distance coefficient and the historical distance coefficient is specifically: multiplying the current distance coefficient by the first weight coefficient α to obtain the first weight distance coefficient; and multiplying the historical distance coefficient by the second weight coefficient. β obtains the second weighted distance coefficient; adding the first weighted distance coefficient and the second weighted distance coefficient to obtain the distance coefficient, where α + β = 1, and α> 0, β> 0. The above-mentioned first weight coefficient and second weight coefficient can be preset or customized. Among the customized weight coefficients, coefficient combinations can be preset, and these coefficient combinations can achieve a predetermined motion effect or can be completely customized. The user can Use a slider to adjust the weight coefficient. When the slider is at the leftmost end, the first weight coefficient is 1 and the second weight coefficient is 0. When the slider is at the center, the first weight coefficient and the second weight coefficient are both 0.5. When the slider is at the far right end, the first weight coefficient is 0 and the second weight coefficient is 1. The user can freely control the value of the weight coefficient through the slider, and at the same time can view the moving image preview generated by the standard image, In order to easily see the effect of the weight coefficient.

After obtaining the distance coefficient, the distances between the target object and the image sensor in multiple times or multiple image frames are calculated using multiple distance coefficients to generate a continuous moving image of the target object.

In this embodiment, calculating the distance coefficient between the target object and the image sensor by using one or more side lengths of the outer frame includes: calculating the target object and the image by using one or more side lengths of the outer frame. The current distance coefficient between the sensors uses the current distance coefficient and the historical distance coefficient to calculate the distance coefficient; in this embodiment, the weight of the current distance coefficient and the historical distance coefficient when calculating the distance coefficient can be adjusted, or The historical distance coefficient calculation method is controlled to achieve different moving image effects.

FIG. 3 is a flowchart of Embodiment 3 of a moving image generating method according to an embodiment of the present disclosure. As shown in FIG. 3, the method may include the following steps:

S301. Use an image sensor to detect the palm;

S302. Identify the smallest rectangle covering the palm.

S303. Calculate a distance coefficient between the palm and the image sensor by using one or more sides of the minimum rectangle.

S304. Use the distance coefficient to generate a moving image of the target object.

In this embodiment, the limited application scenario is that the user moves the palm forward and backward relative to the camera in front of the camera.

When identifying the palm, color features can be used to locate the palm position, segment the palm from the background, and perform feature extraction and recognition on the palm image found and segmented. Specifically, the image sensor is used to obtain the color information of the image and the position information of the color information; compare the color information with preset palm color information; identify the first color information, and the first color information and the preset color information The error of the palm color information is less than the first threshold; the position information of the first color information is used to form the contour of the palm. Preferably, in order to avoid the interference of environmental brightness on color information, the image data of the RGB color space collected by the image sensor can be mapped to the HSV color space, and the information in the HSV color space is used as contrast information. Preferably, the HSV color space is used. The hue value in the color information is used as the color information, the hue information is least affected by the brightness, and the interference of the brightness can be well filtered. Use palm contours to roughly determine the position of the palm, and then extract feature points from the palm of your hand. The method for feature points can use the method described in the first embodiment or any suitable feature point extraction method in the prior art. limit.

After extracting the feature points of the palm image, obtain the boundary feature points of the palm, calculate the X coordinate difference between the two boundary feature points with the furthest X coordinate distance, and calculate the two boundary features with the furthest Y coordinate distance as the length of the rectangle. The difference between the Y coordinates of the points is taken as the length of the rectangle. Use the above method to identify the smallest rectangle covering the palm.

Let the length of the long side of the rectangle be L and the length of the wide side be W. The distance coefficient can be calculated using the following function:

f (x) = Ax ^a

Where x = L + W, A> 0, 0 <a <1.

This function is a power function, and the power exponent is less than 1, so its value becomes larger with the value of x, but the rate of change becomes smaller and smaller. Corresponding to the moving palm image, such an effect can be achieved: the closer the palm is to the lens, the faster the movement speed, and the farther the palm is from the lens, the slower the movement speed. The value of a determines the rate of change of x, and the value of a can be customized by the user, and the implementation of the slider in the second embodiment can also be used, which is not repeated here. It should be noted that the above function is only an example. In practical applications, other suitable functions may be used instead of the above functions. In one implementation, multiple functions and parameters corresponding to the functions may be preset in the system. , The user can select the corresponding function and adjust the corresponding parameters to achieve different moving image effects

In one implementation, the distance coefficient is calculated using the current distance coefficient and the historical distance coefficient:

f '(x) = αf ( x n) + βf (x n-1)

In this embodiment, the target object is the palm, which is applied to the scene where the user moves the palm back and forth in front of the camera, which can bring different motion effects to the palm motion of the user. It should be noted that although the embodiment uses a palm to describe the technical solution, it can be understood that the target object may be any other object, and the technical solution in this embodiment may be used to generate a moving image.

Hereinafter, a moving image generating device of one or more embodiments of the present disclosure will be described in detail. Those skilled in the art can understand that each of these moving image generating devices can be configured by using commercially available hardware components to be configured by the steps taught in this solution.

FIG. 4 is a schematic structural diagram of a first embodiment of an image cropping device according to an embodiment of the present disclosure. As shown in FIG. 4, the device includes a detection module 41, a recognition module 42, a distance coefficient calculation module 43, and an image generation module 44.

A detection module 41, configured to detect a target object using an image sensor;

An identification module 42 for identifying an outer frame of the target object;

A distance coefficient calculation module 43 is configured to calculate a distance coefficient between a target object and an image sensor by using one or more side lengths of the outer frame;

An image generating module 44 is configured to generate a moving image of the target object using the distance coefficient.

The apparatus shown in FIG. 4 can execute the method of the embodiment shown in FIG. 1. For the parts that are not described in detail in this embodiment, refer to the related description of the embodiment shown in FIG. 1. For the implementation process and technical effect of the technical solution, refer to the description in the embodiment shown in FIG. 1, and details are not described herein again.

In the second embodiment of the moving image generating device provided by the embodiment of the present disclosure, based on the embodiment shown in FIG. 4, the module performs the following steps:

The distance coefficient calculation module 43 calculates a current distance coefficient between the target object and the image sensor by using one or more sides of the outer frame, and calculates a distance coefficient by using the current distance coefficient and the historical distance coefficient;

The distance coefficient calculation module 43 includes:

A first distance coefficient calculation module, configured to calculate a current distance coefficient between a target object and an image sensor by using one or more side lengths of the outer frame;

The second distance coefficient calculation module is configured to calculate the distance coefficient by using the current distance coefficient and the historical distance coefficient.

The second distance coefficient calculation module includes:

A first weighted distance coefficient calculation module, configured to multiply the current distance coefficient by the first weighted coefficient to obtain a first weighted distance coefficient;

A second weighted distance coefficient calculation module, configured to multiply the historical distance coefficient by the second weighted coefficient to obtain a second weighted distance coefficient;

A third distance coefficient calculation module is configured to add the first weighted distance coefficient and the second weighted distance coefficient to obtain a distance coefficient.

The device in Embodiment 2 may execute the method in the embodiment shown in FIG. 2. For the parts that are not described in detail in this embodiment, reference may be made to the related description of the embodiment shown in FIG. 2. For the implementation process and technical effect of the technical solution, refer to the description in the embodiment shown in FIG. 2, and details are not described herein again.

In the third embodiment of the moving image generating device provided by the embodiment of the present disclosure, based on the embodiment shown in FIG. 4, the module performs the following steps:

A detection module 41 for detecting a palm using an image sensor;

An identification module 42 for identifying a smallest rectangle covering the palm;

A distance coefficient calculation module 43 configured to calculate a distance coefficient between the palm and the image sensor by using one or more sides of the minimum rectangle;

The detection module 41 includes:

An information acquisition module, configured to acquire color information of an image and position information of the color information using an image sensor;

A comparison module, configured to compare the color information with preset palm color information;

A recognition module, configured to recognize first color information, and an error between the first color information and the preset palm color information is less than a first threshold;

A contour forming module is configured to form a contour of a palm using position information of the first color information.

The moving image generating device in this embodiment may execute the method in the embodiment shown in FIG. 3. For the parts that are not described in detail in this embodiment, reference may be made to the related description of the embodiment shown in FIG. 3. For the implementation process and technical effect of the technical solution, refer to the description in the embodiment shown in FIG. 3, and details are not described herein again.

FIG. 5 is a hardware block diagram illustrating an electronic device according to an embodiment of the present disclosure. As shown in FIG. 5, the electronic device 50 according to an embodiment of the present disclosure includes a memory 51 and a processor 52.

The memory 51 is configured to store non-transitory computer-readable instructions. Specifically, the memory 51 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, and the like.

The processor 52 may be a central processing unit (CPU) or other form of processing unit having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 50 to perform desired functions. In an embodiment of the present disclosure, the processor 52 is configured to run the computer-readable instructions stored in the memory 51 so that the electronic device 50 executes all or part of the foregoing moving image generating method of the embodiments of the present disclosure. step.

Those skilled in the art should understand that, in order to solve the technical problem of how to obtain a good user experience effect, this embodiment may also include well-known structures such as a communication bus and an interface. These well-known structures should also be included in the protection scope of the present disclosure. within.

For detailed descriptions of this embodiment, reference may be made to corresponding descriptions in the foregoing embodiments, and details are not described herein again.

FIG. 6 is a schematic diagram illustrating a computer-readable storage medium according to an embodiment of the present disclosure. As shown in FIG. 6, a computer-readable storage medium 60 according to an embodiment of the present disclosure has non-transitory computer-readable instructions 61 stored thereon. When the non-transitory computer-readable instructions 61 are executed by a processor, all or part of the steps of the foregoing moving image generating method of the embodiments of the present disclosure are performed.

The computer-readable storage medium 60 includes, but is not limited to, optical storage media (for example, CD-ROM and DVD), magneto-optical storage media (for example, MO), magnetic storage media (for example, magnetic tape or mobile hard disk), Non-volatile memory rewritable media (for example: memory card) and media with built-in ROM (for example: ROM box).

FIG. 7 is a schematic diagram illustrating a hardware structure of a terminal device according to an embodiment of the present disclosure. As shown in FIG. 7, the moving image generating terminal 70 includes the foregoing moving image generating device embodiment.

The terminal device may be implemented in various forms, and the terminal device in the present disclosure may include, but is not limited to, such as a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), Mobile terminal devices such as PMPs (portable multimedia players), navigation devices, vehicle-mounted terminal devices, vehicle-mounted display terminals, vehicle-mounted electronic rear-view mirrors, and the like, and fixed terminal devices such as digital TVs, desktop computers, and the like.

As an equivalent alternative implementation, the terminal may further include other components. As shown in FIG. 7, the multi-channel audio processing terminal 70 may include a power supply unit 71, a wireless communication unit 72, an A / V (audio / video) input unit 73, a user input unit 74, a sensing unit 75, and an interface unit 76 , Controller 75, output unit 78, memory 79, and so on. FIG. 7 shows a terminal having various components, but it should be understood that it is not required to implement all the illustrated components, and more or fewer components may be implemented instead.

Among them, the wireless communication unit 72 allows radio communication between the terminal 70 and a wireless communication system or network. The A / V input unit 73 is used to receive audio or video signals. The user input unit 74 may generate key input data according to a command input by the user to control various operations of the terminal device. The sensing unit 75 detects the current state of the terminal 70, the position of the terminal 70, the presence or absence of a user's touch input to the terminal 70, the orientation of the terminal 70, the acceleration or deceleration movement and direction of the terminal 70, and the like, and generates a control for the terminal Command or signal of operation of 70. The interface unit 76 functions as an interface through which at least one external device can connect with the terminal 70. The output unit 78 is configured to provide an output signal in a visual, audio, and / or tactile manner. The memory 79 may store software programs and the like for processing and control operations performed by the controller 75, or may temporarily store data that has been output or is to be output. The memory 79 may include at least one type of storage medium. Moreover, the terminal 70 can cooperate with a network storage device that performs a storage function of the memory 79 through a network connection. The controller 75 generally controls the overall operation of the terminal device. In addition, the controller 75 may include a multimedia module for reproducing or playing back multimedia data. The controller 75 may perform a pattern recognition process to recognize a handwriting input or a picture drawing input performed on the touch screen as a character or an image. The power supply unit 71 receives external power or internal power under the control of the controller 75 and provides appropriate power required to operate each element and component.

Various embodiments of the moving image generation method proposed by the present disclosure may be implemented using a computer-readable medium such as computer software, hardware, or any combination thereof. For hardware implementation, various embodiments of the moving image generation method proposed by the present disclosure can be implemented by using an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), and a programmable logic device (PLD ), A field programmable gate array (FPGA), a processor, a controller, a microcontroller, a microprocessor, an electronic unit designed to perform the functions described herein, and, in some cases, this Various embodiments of the publicly proposed moving image generation method may be implemented in the controller 75. For software implementation, various embodiments of the moving image generation method proposed by the present disclosure may be implemented with a separate software module that allows execution of at least one function or operation. The software codes may be implemented by a software application (or program) written in any suitable programming language, and the software codes may be stored in the memory 79 and executed by the controller 75.

The basic principles of the present disclosure have been described above in conjunction with specific embodiments, but it should be noted that the advantages, advantages, effects, etc. mentioned in this disclosure are merely examples and not limitations, and these advantages, advantages, effects, etc. cannot be considered as Required for various embodiments of the present disclosure. In addition, the specific details of the above disclosure are merely for the purpose of illustration and ease of understanding, and are not limiting, and the above details do not limit the present disclosure to the implementation of the above specific details.

The block diagrams of the devices, devices, equipment, and systems involved in this disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art would realize, these devices, devices, equipment, and systems may be connected, arranged, and configured in any manner. Words such as "including," "including," "having," and the like are open words, meaning "including, but not limited to," and can be used interchangeably with them. As used herein, the words "or" and "and" refer to the words "and / or" and are used interchangeably with each other, unless the context clearly indicates otherwise. The term "such as" as used herein refers to the phrase "such as, but not limited to," and is used interchangeably with it.

In addition, as used herein, an "or" used in an enumeration of items beginning with "at least one" indicates a separate enumeration such that, for example, an "at least one of A, B, or C" enumeration means A or B or C, or AB or AC or BC, or ABC (ie A and B and C). Furthermore, the word "exemplary" does not mean that the described example is preferred or better than other examples.

It should also be noted that, in the system and method of the present disclosure, each component or each step can be disassembled and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions of the present disclosure.

Various changes, substitutions, and alterations to the techniques described herein can be made without departing from the techniques taught by the claims defined below. Further, the scope of the claims of the present disclosure is not limited to the specific aspects of the processes, machines, manufacturing, composition of events, means, methods, and actions described above. A composition, means, method, or action of a process, machine, manufacturing, event that currently exists or is to be developed at a later time may be utilized to perform substantially the same functions or achieve substantially the same results as the corresponding aspects described herein. Accordingly, the appended claims include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or actions.

The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Accordingly, the disclosure is not intended to be limited to the aspects shown herein, but to the broadest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been given for the purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

A moving image generating method includes:

Use the image sensor to detect the target object;

Identifying the outer frame of the target object;

Calculating the distance coefficient between the target object and the image sensor by using one or more sides of the outer frame;

A moving image of the target object is generated using the distance coefficient.
The method of claim 1, wherein the step of calculating a distance coefficient comprises:

The current distance coefficient between the target object and the image sensor is calculated using one or more side lengths of the outer frame, and the distance coefficient is calculated using the current distance coefficient and the historical distance coefficient.
The moving image generating method according to claim 2, wherein the historical distance coefficient is one of the following items:

The distance coefficient between the target object and the image sensor in the previous image frame;

The distance coefficient between the target object and the image sensor at the last moment; and

The average of multiple distance coefficients between the target object and the image sensor in multiple times or multiple frames of images before the current time.
The moving image generating method according to claim 2 or 3, wherein calculating the distance coefficient using the current distance coefficient and the historical distance coefficient comprises:

Multiplying the current distance coefficient by the first weight coefficient to obtain the first weight distance coefficient;

Multiplying the historical distance coefficient by the second weight coefficient to obtain a second weight distance coefficient;

Add the first weighted distance coefficient and the second weighted distance coefficient to obtain the distance coefficient.
The moving image generating method according to claim 4, wherein generating the moving image of the target object using the distance coefficient comprises:

A moving image of the target object is generated using a plurality of distance coefficients.
The moving image generating method according to claim 1 or 2, wherein:

The target object is a palm, and the outer frame is a smallest rectangle covering the palm.
The method for generating a moving image according to claim 6, wherein:

The length of the long side of the rectangle is L, the length of the wide side is W, and the distance coefficient is:

f (x) = Ax a , where x = L + W, A is a real number greater than 0, and 0 <a <1.
The method of claim 6, wherein calculating the distance coefficient using the current distance coefficient and the historical distance coefficient comprises:

f '(x) = αf ( x n) + βf (x n-1)

Where α> 0, β> 0, and α + β = 1, n≥2; f ′ (x) represents the distance coefficient, f (x n ) represents the current distance coefficient, and f (x n-1 ) represents the previous moment Distance factor.
The method of claim 6, wherein detecting the target object using an image sensor comprises:

Use the image sensor to obtain the color information of the image and the position information of the color information;

Comparing the color information with preset palm color information;

Identify the first color information, and an error between the first color information and the preset palm color information is less than a first threshold;

The position information of the first color information is used to form the outline of the palm.
A moving image generating device includes:

A detection module for detecting a target object using an image sensor;

A recognition module, configured to recognize an outer frame of the target object;

A distance coefficient calculation module, configured to calculate a distance coefficient between a target object and an image sensor by using one or more side lengths of the outer frame;

An image generating module is configured to generate a moving image of the target object using the distance coefficient.
An electronic device includes:

At least one processor; and

A memory connected in communication with the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can perform the motion of any one of claims 1-9. Image generation method.
A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the moving image generating method according to any one of claims 1-9.