CN111649690A - Handheld 3D information acquisition equipment and method - Google Patents
Handheld 3D information acquisition equipment and method Download PDFInfo
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- CN111649690A CN111649690A CN202010735593.1A CN202010735593A CN111649690A CN 111649690 A CN111649690 A CN 111649690A CN 202010735593 A CN202010735593 A CN 202010735593A CN 111649690 A CN111649690 A CN 111649690A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
Abstract
The invention provides a handheld 3D information acquisition device and a handheld 3D information acquisition method, wherein the handheld 3D information acquisition device comprises an image acquisition device, a processing device and a display device, wherein the image acquisition device can be handheld and is used for acquiring a group of images of a target object through relative motion; the sensor is used for measuring the moving linear distance when the image acquisition device acquires the images for two times; while the user is moving the image acquisition device: when the moving linear distance does not meet the condition, an alarm is sent to a user; or prompt the user for the distance moved in real time. The invention provides a method for improving the synthesis effect and shortening the synthesis time by limiting the moving distance of a camera for twice photographing.
Description
Technical Field
The invention relates to the technical field of topography measurement, in particular to the technical field of 3D topography measurement.
Background
When performing 3D measurements, it is necessary to first acquire 3D information. The currently common method includes using a machine vision mode to collect pictures of an object from different angles, and matching and splicing the pictures to form a 3D model. When pictures at different angles are collected, a plurality of cameras can be arranged at different angles of the object to be detected, and the pictures can be collected from different angles through rotation of a single camera or a plurality of cameras. However, both of these methods involve problems of synthesis speed and synthesis accuracy. The synthesis speed and the synthesis precision are a pair of contradictions to some extent, and the improvement of the synthesis speed can cause the final reduction of the 3D synthesis precision; to improve the 3D synthesis accuracy, the synthesis speed needs to be reduced, and more pictures need to be synthesized.
In the prior art, in order to simultaneously improve the synthesis speed and the synthesis precision, the synthesis is generally realized by a method of optimizing an algorithm. And the art has always considered that the approach to solve the above problems lies in the selection and updating of algorithms, and no method for simultaneously improving the synthesis speed and the synthesis precision from other angles has been proposed so far. However, the optimization of the algorithm has reached a bottleneck at present, and before no more optimal theory appears, the improvement of the synthesis speed and the synthesis precision cannot be considered.
In the prior art, it has also been proposed to use empirical formulas including rotation angle, object size, object distance to define camera position, thereby taking into account the speed and effect of the synthesis. However, in practical applications it is found that: unless a precise angle measuring device is provided, the user is insensitive to the angle and is difficult to accurately determine the angle; the size of the target is difficult to accurately determine, and particularly, the target needs to be frequently replaced in certain application occasions, each measurement brings a large amount of extra workload, and professional equipment is needed to accurately measure irregular targets. The measured error causes the camera position setting error, thereby influencing the acquisition and synthesis speed and effect; accuracy and speed need to be further improved.
Therefore, the following technical problems are urgently needed to be solved: firstly, the synthesis speed and the synthesis precision can be greatly improved simultaneously; the operation is convenient, professional equipment is not needed, excessive measurement is not needed, and the position of the camera can be obtained quickly.
Disclosure of Invention
In view of the above, the present invention has been developed to provide a collecting device that overcomes, or at least partially solves, the above-mentioned problems.
The embodiment of the invention provides a handheld 3D information acquisition device and a handheld 3D information acquisition method, wherein an image acquisition device can be held by a hand and is used for acquiring a group of images of a target object through relative motion;
the sensor is used for measuring the moving linear distance when the image acquisition device acquires the images for two times;
while the user is moving the image acquisition device: when the moving linear distance does not meet the condition, an alarm is sent to a user; or prompt the user for the distance moved in real time.
Optionally, during the relative movement, the collecting position of the image collecting device meets the following conditions:
wherein L is the linear distance of the optical center of the image acquisition device at two adjacent acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width of the photosensitive element of the image acquisition device; t is the distance from the photosensitive element of the image acquisition device to the surface of the target along the optical axis; to adjust the coefficients.
Alternatively, < 0.410.
Alternatively, < 0.356; or < 0.311; or < 0.284; or < 0.261; or < 0.241; or < 0.107.
Optionally, the condition is a condition on L.
Optionally, the method further comprises prompting the user of the maximum movable distance L in real time.
Optionally, the image acquisition device is a mobile terminal.
Optionally, the system further comprises a processor for performing 3D synthesis according to a plurality of images in the set of images to generate a 3D model of the object.
Optionally, the image acquisition device is a visible light band, an infrared light band, and/or a full band.
Another embodiment of the invention also provides a payment device or method, and any one of the devices or methods is used.
The invention also provides a 3D synthesis device or method using any one of the above devices or methods.
Another embodiment of the present invention further provides an identification/comparison apparatus or method using any of the above devices or methods.
Another embodiment of the invention also provides an accessory manufacturing method or device, and any one of the devices or methods is used.
Invention and technical effects
1. It is first proposed to improve both the synthesis speed and the synthesis accuracy by increasing the way in which the background plate rotates together with the camera.
2. By optimizing the position of the camera for collecting the picture, the synthesis speed and the synthesis precision can be ensured to be improved simultaneously. And when the position is optimized, the angle and the target size do not need to be measured, and the applicability is stronger.
3. A3D synthesis algorithm matched with the acquisition mode is provided, and the speed and the effect of 3D modeling can be improved.
4. A method for improving the synthesis effect and shortening the synthesis time by limiting the moving distance of the camera for twice photographing is provided.
5. The acquisition position of the user when the user holds the acquisition equipment is prompted through measuring the distance change when the image is acquired, the user is guaranteed to carry out 3D acquisition within a preset acquisition condition range, and the acquisition efficiency and the synthesis precision of the handheld equipment can be improved.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a schematic diagram of an embodiment of a handheld image capturing device for capturing images;
the correspondence of reference numerals to the respective components is as follows:
1 target object, 2 object stage, 4 image acquisition device.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
To solve the above technical problem, an embodiment of the present invention provides a handheld 3D information acquisition device, which includes an image acquisition apparatus. The handheld image acquisition device acquires a group of images of the target object through the relative movement of an acquisition area of the image acquisition device and the target object; the handheld image acquisition device drives an acquisition area of the image acquisition device to move relative to the target object. The collection area is the effective field range of the image collection device.
The mobile device of the acquisition area is a random motion structure
As shown in fig. 1, the movement of the capturing area is not regular, for example, the image capturing device 4 can be held by hand to capture images around the target 1, and it is difficult to move in a strict track, and the movement track of the image capturing device 4 is difficult to predict accurately. Therefore, in this case, how to ensure that the captured images can be accurately and stably synthesized into the 3D model is a difficult problem, which has not been mentioned yet. A more common approach is to take multiple photographs, with redundancy in the number of photographs to address this problem. However, the synthesis results are not stable. Although there are some ways to improve the composite effect by limiting the rotation angle of the camera, in practice, the user is not sensitive to the angle, and even if the preferred angle is given, the user is difficult to operate in the case of hand-held shooting. Therefore, the invention provides a method for improving the synthesis effect and shortening the synthesis time by limiting the moving distance of the camera for twice photographing.
For example, in the process of face recognition, a user can hold the mobile terminal to shoot around the face of the user in a moving mode. As long as the experience requirements (specifically described below) of the photographing position are met, the 3D model of the face can be accurately synthesized, and at this time, the face recognition can be realized by comparing with the standard model stored in advance. For example, the handset may be unlocked, or payment verification may be performed.
In the case of irregular movement, a sensor may be provided in the mobile terminal or the image capturing device 4, and a linear distance moved by the image capturing device 4 during two times of photographing may be measured by the sensor, and when the moving distance does not satisfy the above-mentioned experience condition with respect to L (specifically, the following condition), an alarm may be issued to the user. The alarm comprises sounding or lighting an alarm to the user. Of course, the distance moved by the user and the maximum movable distance L may also be displayed on the screen of the mobile phone or prompted by voice in real time when the user moves the image capturing device 4. The sensor that accomplishes this function includes: a range finder, a gyroscope, an accelerometer, a positioning sensor, and/or combinations thereof.
Light source
Typically, the light sources are distributed around the lens of the image capturing device 4, for example, the light sources are ring-shaped LED lamps around the lens. Since in some applications the object to be acquired is a human body, the intensity of the light source needs to be controlled to avoid discomfort to the human body. In particular, a light softening means, for example a light softening envelope, may be arranged in the light path of the light source. Or the LED surface light source is directly adopted, so that the light is soft, and the light is more uniform. Preferably, an OLED light source can be adopted, the size is smaller, the light is softer, and the flexible OLED light source has the flexible characteristic and can be attached to a curved surface. The light source may also be positioned at other locations that provide uniform illumination of the target. The light source can also be an intelligent light source, namely, the light source parameters are automatically adjusted according to the conditions of the target object 1 and the ambient light.
Image acquisition device setting method
Handheld image acquisition device 4 rotates around object 1, and when carrying out 3D collection, image acquisition device 4 changes for object 1 in different collection position optical axis directions, and two adjacent image acquisition device 4's position this moment, or two adjacent collection positions of image acquisition device 4 satisfy the following condition:
wherein L is the linear distance between the optical centers of the two adjacent acquisition position image acquisition devices 4; f is the focal length of the image acquisition device 4; d is the rectangular length or width of the photosensitive element (CCD) of the image acquisition device 4; t is the distance from the photosensitive element of the image acquisition device 4 to the surface of the target object 1 along the optical axis; to adjust the coefficients.
When the two positions are along the length direction of the photosensitive element of the image acquisition device 4, d is a rectangular length; when the two positions are along the width direction of the photosensitive element of the image pickup device 4, d takes a rectangular width.
When the image pickup device 4 is in any one of the two positions, the distance from the photosensitive element to the surface of the object along the optical axis is taken as T. In addition to this method, in another case, L is An、An+1Linear distance between optical centers of two image capturing devices, and An、An+1Two image capturing devices 4 adjacent to each other An-1、 An+2Two image capturing devices 4 and An、An+1The distances from the respective photosensitive elements of the two image acquisition devices 4 to the surface of the target 1 along the optical axis are respectively Tn-1、Tn、Tn+1、Tn+2，T＝(Tn-1+Tn+Tn+1+Tn+2)/4. Of course, the average value may be calculated by using more positions than the adjacent 4 positions.
As mentioned above, L should be a straight-line distance between the optical centers of the two image capturing devices 4, but since the optical center positions of the image capturing devices 4 are not easily determined in some cases, the center of the photosensitive element of the image capturing device 4, the geometric center of the image capturing device 4, the axial center of the connection between the image capturing device 4 and the pan/tilt head (or platform, support), the center of the proximal or distal surface of the lens may be used instead in some cases, and the error caused by the displacement is found to be within an acceptable range through experiments, and therefore, the range is also within the protection scope of the present invention.
In general, parameters such as object size and angle of view are used as means for estimating the position of a camera in the prior art, and the positional relationship between two cameras is also expressed in terms of angle. Because the angle is not well measured in the actual use process, it is inconvenient in the actual use. Also, the size of the object may vary with the variation of the measurement object. For example, when the head of a child is collected after 3D information on the head of an adult is collected, the head size needs to be measured again and calculated again. The inconvenient measurement and the repeated measurement bring errors in measurement, thereby causing errors in camera position estimation. According to the scheme, the experience conditions required to be met by the position of the camera are given according to a large amount of experimental data, so that the problem that the measurement is difficult to accurately measure the angle is solved, and the size of an object does not need to be directly measured. In the empirical condition, d and f are both fixed parameters of the camera, and corresponding parameters can be given by a manufacturer when the camera and the lens are purchased without measurement. And T is only a straight line distance, and can be conveniently measured by using a traditional measuring method, such as a ruler and a laser range finder. Therefore, the empirical formula of the invention enables the preparation process to be convenient and fast, and simultaneously improves the arrangement accuracy of the camera position, so that the camera can be arranged in an optimized position, thereby simultaneously considering the 3D synthesis precision and speed, and the specific experimental data is shown in the following.
Experiments were conducted using the apparatus of the present invention, and the following experimental results were obtained.
The camera lens is replaced, and the experiment is carried out again, so that the following experiment results are obtained.
The camera lens is replaced, and the experiment is carried out again, so that the following experiment results are obtained.
From the above experimental results and a lot of experimental experiences, it can be derived that the value should satisfy <0.603, and at this time, a part of the 3D model can be synthesized, although a part cannot be automatically synthesized, it is acceptable in the case of low requirements, and the part which cannot be synthesized can be compensated manually or by replacing the algorithm. Particularly, when the value satisfies <0.410, the balance between the synthesis effect and the synthesis time can be optimally taken into consideration; to obtain better synthesis results, <0.356 can be chosen, where the synthesis time will increase, but the synthesis quality is better. Of course, <0.311 may be selected to further improve the effect of the synthesis. And 0.681, the synthesis is not possible. It should be noted that the above ranges are only preferred embodiments and should not be construed as limiting the scope of protection.
Moreover, as can be seen from the above experiment, for the determination of the photographing position of the camera, only the camera parameters (focal length f, CCD size) and the distance T between the camera CCD and the object surface need to be obtained according to the above formula, which makes it easy to design and debug the device. Since the camera parameters (focal length f, CCD size) are determined at the time of purchase of the camera and are indicated in the product description, they are readily available. Therefore, the camera position can be easily calculated according to the formula without carrying out complicated view angle measurement and object size measurement. Particularly, in some occasions, the lens of the camera needs to be replaced, and then the position of the camera can be obtained by directly replacing the conventional parameter f of the lens and calculating; similarly, when different objects are collected, the measurement of the size of the object is complicated due to the different sizes of the objects. By using the method of the invention, the position of the camera can be determined more conveniently without measuring the size of the object. And the camera position determined by the invention can give consideration to both the synthesis time and the synthesis effect. Therefore, the above-described empirical condition is one of the points of the present invention.
The above data are obtained by experiments for verifying the conditions of the formula, and do not limit the invention. Without these data, the objectivity of the formula is not affected. Those skilled in the art can adjust the equipment parameters and the step details as required to perform experiments, and obtain other data which also meet the formula conditions.
The rotation movement of the invention is that the front position collection plane and the back position collection plane are crossed but not parallel in the collection process, or the optical axis of the front position image collection device and the optical axis of the back position image collection device are crossed but not parallel. That is, the capture area of the image capture device moves around or partially around the target, both of which can be considered as relative rotation. Although the embodiment of the present invention exemplifies more orbital rotation, it should be understood that the limitation of the present invention can be used as long as the non-parallel motion between the acquisition region of the image acquisition device and the target object is rotation. The scope of the invention is not limited to the embodiment with track rotation.
The adjacent acquisition positions refer to two adjacent positions on a movement track where acquisition actions occur when the image acquisition device moves relative to a target object. This is generally easily understood for the image acquisition device movements. However, when the target object moves to cause relative movement between the two, the movement of the target object should be converted into the movement of the target object, which is still, and the image capturing device moves according to the relativity of the movement. And then measuring two adjacent positions of the image acquisition device in the converted movement track.
3D synthesis method
After the image acquisition equipment acquires images of a target object in multiple directions through the image acquisition device 4, the images are transmitted to the processor in a data transmission mode. The processor may be located locally or the image may be uploaded to a cloud platform using a remote processor. The synthesis of the 3D model is performed in the processor using the following method.
When the collected pictures are used for 3D synthesis, the existing algorithm can be adopted, and the optimized algorithm provided by the invention can also be adopted, and the method mainly comprises the following steps:
step 1: and performing image enhancement processing on all input photos. The contrast of the original picture is enhanced and simultaneously the noise suppressed using the following filters.
In the formula: g (x, y) is the gray value of the original image at (x, y), and f (x, y) is the gray value of the original image at the position enhanced by the Wallis filterValue of mgIs the local gray average value, s, of the original imagegIs the local standard deviation of gray scale of the original image, mfFor the transformed image local gray scale target value, sfC ∈ (0, 1) is the spreading constant of the image variance, and b ∈ (0, 1) is the image brightness coefficient constant.
The filter can greatly enhance image texture modes of different scales in an image, so that the quantity and the precision of feature points can be improved when the point features of the image are extracted, and the reliability and the precision of a matching result are improved in photo feature matching.
Step 2: and extracting feature points of all input photos, and matching the feature points to obtain sparse feature points. And extracting and matching feature points of the photos by adopting a SURF operator. The SURF feature matching method mainly comprises three processes of feature point detection, feature point description and feature point matching. The method uses a Hessian matrix to detect characteristic points, a Box filter (Box Filters) is used for replacing second-order Gaussian filtering, an integral image is used for accelerating convolution to improve the calculation speed, and the dimension of a local image characteristic descriptor is reduced to accelerate the matching speed. The method mainly comprises the steps of firstly, constructing a Hessian matrix, generating all interest points for feature extraction, and constructing the Hessian matrix for generating stable edge points (catastrophe points) of an image; secondly, establishing scale space characteristic point positioning, comparing each pixel point processed by the Hessian matrix with 26 points in a two-dimensional image space and a scale space neighborhood, preliminarily positioning a key point, filtering the key point with weak energy and the key point with wrong positioning, and screening out a final stable characteristic point; and thirdly, determining the main direction of the characteristic points by adopting the harr wavelet characteristics in the circular neighborhood of the statistical characteristic points. In a circular neighborhood of the feature points, counting the sum of horizontal and vertical harr wavelet features of all points in a sector of 60 degrees, rotating the sector at intervals of 0.2 radian, counting the harr wavelet feature values in the region again, and taking the direction of the sector with the largest value as the main direction of the feature points; and fourthly, generating a 64-dimensional feature point description vector, and taking a 4-by-4 rectangular region block around the feature point, wherein the direction of the obtained rectangular region is along the main direction of the feature point. Each subregion counts haar wavelet features of 25 pixels in both the horizontal and vertical directions, where both the horizontal and vertical directions are relative to the principal direction. The haar wavelet features are in 4 directions of the sum of the horizontal direction value, the vertical direction value, the horizontal direction absolute value and the vertical direction absolute value, and the 4 values are used as feature vectors of each sub-block region, so that a total 4 x 4-64-dimensional vector is used as a descriptor of the Surf feature; and fifthly, matching the characteristic points, wherein the matching degree is determined by calculating the Euclidean distance between the two characteristic points, and the shorter the Euclidean distance is, the better the matching degree of the two characteristic points is.
And step 3: inputting matched feature point coordinates, resolving sparse human face three-dimensional point cloud and position and posture data of a photographing camera by using a light beam method adjustment, namely obtaining model coordinate values of the sparse human face model three-dimensional point cloud and the position; and performing multi-view photo dense matching by taking the sparse feature points as initial values to obtain dense point cloud data. The process mainly comprises four steps: stereo pair selection, depth map calculation, depth map optimization and depth map fusion. For each image in the input data set, we select a reference image to form a stereo pair for use in computing the depth map. Therefore, we can get rough depth maps of all images, which may contain noise and errors, and we use its neighborhood depth map to perform consistency check to optimize the depth map of each image. And finally, carrying out depth map fusion to obtain the three-dimensional point cloud of the whole scene.
And 4, step 4: and reconstructing a human face curved surface by using the dense point cloud. The method comprises the steps of defining an octree, setting a function space, creating a vector field, solving a Poisson equation and extracting an isosurface. And obtaining an integral relation between the sampling point and the indicating function according to the gradient relation, obtaining a vector field of the point cloud according to the integral relation, and calculating the approximation of the gradient field of the indicating function to form a Poisson equation. And (3) solving an approximate solution by using matrix iteration according to a Poisson equation, extracting an isosurface by adopting a moving cube algorithm, and reconstructing a model of the measured point cloud.
And 5: and (4) fully-automatic texture mapping of the human face model. And after the surface model is constructed, texture mapping is carried out. The main process comprises the following steps: texture data is obtained to reconstruct a surface triangular surface grid of a target through an image; and secondly, reconstructing the visibility analysis of the triangular surface of the model. Calculating a visible image set and an optimal reference image of each triangular surface by using the calibration information of the image; and thirdly, clustering the triangular surface to generate a texture patch. Clustering the triangular surfaces into a plurality of reference image texture patches according to the visible image set of the triangular surfaces, the optimal reference image and the neighborhood topological relation of the triangular surfaces; and fourthly, automatically sequencing the texture patches to generate texture images. And sequencing the generated texture patches according to the size relationship of the texture patches to generate a texture image with the minimum surrounding area, and obtaining the texture mapping coordinate of each triangular surface.
It should be noted that the above algorithm is an optimization algorithm of the present invention, the algorithm is matched with the image acquisition condition, and the use of the algorithm takes account of the time and quality of the synthesis, which is one of the inventions of the present invention. Of course, it can be implemented using conventional 3D synthesis algorithms in the prior art, except that the synthesis effect and speed are somewhat affected.
Accessory matching and making
After 3D information of the target object is collected and the 3D model is synthesized, accessories matched with the target object can be manufactured for the target object according to the 3D data.
Such as making glasses for the user to fit the face. On the basis of meeting the limit of the experience condition, acquiring a plurality of pictures of the head of the user in different directions; and (3) synthesizing the plurality of photos into a 3D model by using 3D synthesis software, wherein the adopted method can use a common 3D picture matching algorithm. And after obtaining the 3D mesh model, adding texture information to form a head 3D model. And selecting a proper glasses frame for the user according to the relevant position size of the 3D head model, such as cheek width, nose bridge height, auricle size and the like.
Besides glasses, a variety of accessories such as hats, gloves, artificial limbs, and the like can be designed for users. It is also possible to design the object with accessories that fit it, for example, to design the profiled part with a closely wrapped package, etc.
Target identification and comparison
The 3D information of multiple regions of the target obtained in the above embodiments can be used for comparison, for example, for identification of identity. Firstly, the scheme of the invention is utilized to acquire the 3D information of the face and the iris of the human body, and the information is stored in a server as standard data. When the system is used, for example, when the system needs to perform identity authentication to perform operations such as payment and door opening, the 3D acquisition device can be used for acquiring and acquiring the 3D information of the face and the iris of the human body again, the acquired information is compared with standard data, and if the comparison is successful, the next action is allowed. It can be understood that the comparison can also be used for identifying fixed assets such as antiques and artworks, namely, the 3D information of a plurality of areas of the antiques and the artworks is firstly acquired as standard data, when the identification is needed, the 3D information of the plurality of areas is acquired again and compared with the standard data, and the authenticity is identified.
Although the image capturing device captures an image in the above embodiments, the image capturing device is not understood to be applicable to only a group of pictures made of a single picture, and this is merely an illustrative manner for facilitating understanding. The image acquisition device can also acquire video data, and directly utilize the video data or intercept images from the video data to carry out 3D synthesis. However, the shooting position of the corresponding frame of the video data or the captured image used in the synthesis still satisfies the above empirical formula.
The target object, and the object all represent objects for which three-dimensional information is to be acquired. The object may be a solid object or a plurality of object components. For example, the head, hands, etc. The three-dimensional information of the target object comprises a three-dimensional image, a three-dimensional point cloud, a three-dimensional grid, a local three-dimensional feature, a three-dimensional size and all parameters with the three-dimensional feature of the target object. Three-dimensional in the present invention means having XYZ three-direction information, particularly depth information, and is essentially different from only two-dimensional plane information. It is also fundamentally different from some definitions, which are called three-dimensional, panoramic, holographic, three-dimensional, but actually comprise only two-dimensional information, in particular not depth information.
The capture area in the present invention refers to a range in which an image capture device (e.g., a camera) can capture an image. The image acquisition device can be a CCD, a CMOS, a camera, a video camera, an industrial camera, a monitor, a camera, a mobile phone, a tablet, a notebook, a mobile terminal, a wearable device, intelligent glasses, an intelligent watch, an intelligent bracelet and all devices with image acquisition functions.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components in an apparatus in accordance with embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications consistent with the principles of the invention may be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.
Claims (10)
1. A handheld 3D information acquisition device and method are characterized in that:
an image capture device, capable of being hand-held, for capturing a set of images of a target object by relative movement;
the sensor is used for measuring the moving linear distance when the image acquisition device acquires the images for two times;
while the user is moving the image acquisition device: when the moving linear distance does not meet the condition, an alarm is sent to a user; or prompt the user for the distance moved in real time.
2. The apparatus or method of claim 1, wherein:
in the relative movement process, the acquisition position of the image acquisition device meets the following conditions:
<0.603
wherein L is the linear distance of the optical center of the image acquisition device at two adjacent acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width of the photosensitive element of the image acquisition device; t is the distance from the photosensitive element of the image acquisition device to the surface of the target along the optical axis; to adjust the coefficients.
3. The apparatus or method of claim 2, wherein: < 0.410.
4. The apparatus or method of claim 2, wherein: < 0.356; or < 0.311; or < 0.284; or < 0.261; or < 0.241; or < 0.107.
5. The apparatus or method of claim 2, wherein: the condition is a condition for L.
6. The apparatus or method of claim 5, wherein: and prompting the user of the movable maximum distance L in real time.
7. The apparatus or method of claim 1, wherein: the image acquisition device is a mobile terminal.
8. The apparatus or method of claim 1, wherein: a processor is also included for 3D synthesis from a plurality of the set of images to generate a 3D model of the object.
9. The apparatus or method of claim 1, wherein: the image acquisition device is a visible light band, an infrared light band and/or a full band.
10. A payment apparatus or method, or 3D synthesis device or method, using an apparatus or method as claimed in any one of claims 1 to 9; or an identification/alignment device or method; or adjunct manufacturing methods or apparatus.
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