CN101894379A - Method and device for segmentation of characteristic point motion for large interframe motion video - Google Patents
Method and device for segmentation of characteristic point motion for large interframe motion video Download PDFInfo
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Abstract
The invention provides a method for the segmentation of characteristic point motion for a large interframe motion video, which comprises the following steps of: extracting characteristic points from two adjacent video frames in the large interframe motion video and establishing characteristic vector description on all characteristic points; obtaining matching characteristic point pairs between the two adjacent video frames according to the characteristic points and the corresponding characteristic vector description; and performing the segmentation of the characteristic point motion by utilizing a voting method according to plane homography transformation. The invention provides a motion model which can describe the motion of plane objects and objects which are approximate to the planes effectively by utilizing the plane homography transformation, so that the segmentation of the characteristic point motion in complex scenes is realized.
Description
Technical field
The present invention relates to technical field of image processing, particularly a kind of unique point motion segmentation method and device at big interframe movement video.
Background technology
Video features point motion segmentation is an important and basic problem of computer vision field.It all is widely used at a lot of other video correlative technology fields, as object-based video coding, based on three-dimensional video-frequency generation, the object identification cut apart, image retrieval etc.Just because of video features point motion segmentation numerous video correlation techniques are had crucial effects, video features point motion segmentation technology has high scientific research and using value.
The technical finesse of video features point motion segmentation to as if one section video sequence, promptly two or more continuous video frames.Its target is that the motion of the unique point in the adjacent video frames is reasonably classified, and the unique point on the same movement object is assigned in the same class, and the unique point on the different objects is assigned in the inhomogeneity.It comprises foundation and two key steps of unique point classification of motions of unique point motion.
The foundation of unique point motion generally is divided into feature point extraction and two parts are asked in motion.Feature point extraction is meant from image extracts the image-region with certain geometry or color characteristic, and locatees this zone in image coordinate system, sets up the descriptor to this unique point simultaneously.It is the most close unique point of zone searching descriptor approaching with this frame characteristic point position in consecutive frame that motion is asked for, and the difference of two characteristic point positions has promptly characterized the unique point motion.Yet for big interframe movement video, because two frame difference are bigger, the motion of unique point is bigger, and therefore traditional motion acquiring method is difficult to the movement position that finds unique point correct.
After the unique point motion is set up, also need difference according to the unique point motion, motion is classified to unique point, thereby realizes the unique point motion segmentation.The target of unique point classification of motions is that the motion of the unique point on the different motion object is separated fully, yet, the motion of the various piece of same object on image may have nothing in common with each other, unique point on the different objects also close or identical motion may occur, and these bring bigger difficulty all for the unique point classification of motions.
Summary of the invention
The objective of the invention is to solve the unique point motion segmentation problem in the big interframe movement video.On the unique point extraction, the method for use characteristic coupling of the present invention realizes the unique point extraction to big interframe movement video.On the unique point classification of motions, the present invention utilizes the plane homograph, has proposed effectively to portray the motion model of plane and almost plane object of which movement, and then realizes the unique point motion segmentation of complex scene.
For achieving the above object, one aspect of the present invention has proposed a kind of unique point motion segmentation method at big interframe movement video, may further comprise the steps: the two adjacent video frames in the big interframe movement video is carried out feature point extraction respectively, and set up the proper vector of all unique points is described; Right according to the matching characteristic point that described unique point and characteristic of correspondence vector description obtain between the described two adjacent video frames; With according to the plane homograph, utilize the method for ballot to carry out cutting apart of unique point motion.
The present invention has also proposed a kind of unique point motion segmentation device at big interframe movement video on the other hand, comprise: the feature point extraction module, be used for the two adjacent video frames in the big interframe movement video is carried out feature point extraction respectively, and set up the proper vector of all unique points is described; Matching characteristic point is to acquisition module, and it is right to be used for the matching characteristic point that obtains between the described two adjacent video frames according to described unique point and characteristic of correspondence vector description; With the motion segmentation module, be used for according to the plane homograph, utilize the method for ballot to carry out cutting apart of unique point motion.
The method of use characteristic point coupling of the present invention is asked for motion, in consecutive frame, carry out the feature point extraction second time, afterwards the unique point of two interframe is carried out characteristic matching,, thereby realized the foundation of the unique point motion of big interframe movement video with the motion of the coordinate difference characteristic feature of matching characteristic point.
In addition, the unique point classification of motions method that the present invention proposes, can utilize the plane homograph, good portrayal has been carried out in the motion of planar object in the scene or almost plane object, make the classification of motions of unique point on this type objects has been obtained good effect.Simultaneously, unique point classification of motions method of the present invention can realize the automatic removal of error characteristic point motion has been improved the robustness that algorithm is asked for wrong motion effectively.
Aspect that the present invention adds and advantage part in the following description provide, and part will become obviously from the following description, or recognize by practice of the present invention.
Description of drawings
Above-mentioned and/or additional aspect of the present invention and advantage are from obviously and easily understanding becoming the description of embodiment below in conjunction with accompanying drawing, wherein:
Fig. 1 is a plane homograph synoptic diagram;
Fig. 2 is the unique point motion segmentation method process flow diagram at big interframe movement video of the embodiment of the invention;
Fig. 3 is the unique point motion segmentation structure drawing of device at big interframe movement video of the embodiment of the invention.
Embodiment
Describe embodiments of the invention below in detail, the example of described embodiment is shown in the drawings, and wherein identical from start to finish or similar label is represented identical or similar elements or the element with identical or similar functions.Below by the embodiment that is described with reference to the drawings is exemplary, only is used to explain the present invention, and can not be interpreted as limitation of the present invention.
In order clearer understanding to be arranged to the present invention, below the SIFT feature extraction algorithm and the plane homograph that at first will adopt to the present invention simply introduce:
1, SIFT feature extraction algorithm
The SIFT feature extraction algorithm can find the texture region with feature in image, and accurately calculates the two-dimensional coordinate of this zone in image, should the zone with the representation of concept of unique point, and with high dimensional feature vector description unique point.In theory, this is described in unique point generation translation, will can not change during flexible or rotation, and simultaneously, this feature changes the image light and shade also very strong unchangeability.
2, plane homograph
For the point on certain two dimensional surface in the three dimensions, the plane homograph has been described the relation of these o'clocks to two two-dimensional camera plane projections.Specifically, in the three dimensions, the point on certain plane, it satisfies following relation between the three-dimensional homogeneous coordinates of projection on two different camera plane:
Wherein,
With
Be the homogeneous coordinates of this some projection on two camera plane, H is by two cameras decisions of the plane in the three dimensions and this, and it is the plane homograph that the present invention discusses, retraining on the plane have a few.9 elements are arranged in the matrix H, but in fact have only 8 degree of freedom, therefore 4 pairs of mutual incoherent unique points are estimated just finishing right H on the need plane.As shown in Figure 1, be plane homograph synoptic diagram.In our research, the object in the scene is considered to distant apart from camera, and perhaps object has only a face to be taken by camera, and under this hypothesis, the object in the scene can be approximately a plane, and their motion can be described with the plane homograph.
As shown in Figure 2, the unique point motion segmentation method process flow diagram at big interframe movement video for the embodiment of the invention may further comprise the steps:
Method in the video features point motion segmentation that the present invention proposes as shown in Figure 2, comprises following two steps:
Step S201 carries out the SIFT feature point extraction to adjacent two frames in the video, and utilizes the feature descriptor of SIFT unique point to set up the coupling of two interframe unique points.Need to prove, adopt the SIFT Feature Points Extraction in embodiments of the present invention, other Feature Points Extraction also can be applied among the present invention but those skilled in the art should recognize employing, therefore also should be included within protection scope of the present invention.This step specifically comprises following two steps:
(11) extract all feature texture regions (unique point) of adjacent two frames of video sequence based on the feature extraction algorithm of SIFT, set up on the one hand the proper vector of all unique points is described, on the other hand the image coordinate of unique point is accurately located.
(12) describe according to the proper vector of unique point, utilize the characteristic matching algorithm to seek the matching relationship of adjacent two frame unique points, make the unique point of describing the same space point in two frames realize coupling, it is right to obtain matching characteristic point.
Step S202 according to the plane homograph, utilizes the method for ballot that the matching characteristic point is classified, and removes wrong coupling, realizes the unique point motion segmentation, specifically comprises following two steps:
(21) right from the rational extracting part branch of matching characteristic point centering, carry out the initial plane homograph and estimate.
(22) all initial plane homograph ballots of all matching characteristic point subtends, remove wrong plane homograph according to voting results, the plane homograph that merges the expression same movement, and with correct matching characteristic point to distributing to corresponding plane homograph, the matching characteristic point that each plane homograph comprises moves to representing of a sort unique point, thereby realizes the unique point motion segmentation.
In order clearer understanding to be arranged to the above embodiment of the present invention, below for using the embodiment that said method generates video frame depth chart, wherein with adjacent two frame of video A, B is an example, describes the process of unique point motion segmentation.
At first, to A, B two frame of video are carried out the SIFT feature point extraction respectively.Every frame all obtains the unique point of some, and all corresponding high dimension vector of each unique point is described this unique point.
Secondly, the unique point in two frames is carried out Feature Points Matching.At first define the Euclidean distance of the distance of any two unique points for their corresponding high dimension vectors.Secondly, for a unique point in the A frame, calculate its with the B frame in the distance of middle arbitrary characteristics point, if certain unique point satisfies following two conditions in the B frame, then this unique point is considered as the candidate matches unique point of unique point in the A frame.Two conditions are described below: 1) this unique point is from the nearest unique point of A frame unique point in all unique points of B frame; 2) distance of two unique points (minimum distance) and time in-plant ratio are less than TQ (generally getting between the 0.6-0.8).Once more, transposing A frame and B frame carry out aforesaid operations one time, again if two unique points in two frames all are judged as the other side the candidate matches unique point of oneself in twice operation, then two unique points are that final matching characteristic point is right, and the position difference of two unique points has been described the motion of unique point.
Once more, carry out the estimation of initial plane homograph.In our estimation, suppose that at first the unique point motion on the same object is more approaching, because any object is in the process of motion, motion all is a continually varying on it, bigger sudden change can only be created on the different objects.Based on such hypothesis, we at first estimate an initial homograph from each unique point.Estimation approach is, take out in a unique point and other 5 these frames with the unique point of its two dimensional motion difference minimum totally 6 unique points carry out a secondary flat homograph and estimate, the conversion of estimating as the initial plane homograph.
At last, the ballot of unique point subtend initial plane homograph realizes the unique point motion segmentation.In these initial transformations that we estimate, if the unique point of using to from different moving object, this initial transformation will be full of prunes so; If from same object, what two so such initial transformations were described is same moving object to the unique point that two initial transformations are used, and has redundancy to all.At first, we detect a unique point to whether satisfying a plane homograph with following formula.
Wherein,
With
Be unique point to the homogeneous coordinates of Ck in two frames, τ is a threshold value, τ desirable 3～7 in embodiments of the present invention.If unique point satisfies initial homograph Hl to Ck, think that then Ck to the Hl ballot once.After every pair of matching characteristic point is all finished above-mentioned detection to each initial transformation, will comprise the ballot paper of some in the ballot box of initial transformation correspondence.Analyze voting process, will find that voting results have following two character: 1) every pair of matching characteristic point can be to a plurality of initial transformation ballots; 2) each initial transformation only corresponding one from certain ballot paper to matching characteristic point.After the ballot, we will merge initial transformation, and above ballot paper is right from identical unique point if two initial transformations have p% (p generally gets 70～80), and what think then that these two conversion may describe is the motion of same object, therefore they are merged, ballot paper also merges together.Like this, through after this step, the number of conversion descends to some extent, more near the number of real motion in the scene.After combined transformation, the right classification of matching characteristic point is still indeterminate, because a pair of unique point may be to a plurality of conversion ballots, and through after merging, may repeat to same conversion.Therefore, in order to determine the right classification of matching characteristic point, the poll of our each conversion ballot of calculated characteristics point subtend thinks that it belongs to that maximum conversion of ballot.Unique point for erroneous matching is right, because the motion of its description do not exist in scene, so its ballot negligible amounts.The present invention will vote unique point that number of times is less than q time (q generally gets 3-5) to thinking wrong coupling, directly remove from the result.Finally, all unique points that comprise in each conversion have promptly realized the unique point motion segmentation to belonging to same class.
As shown in Figure 3, be the unique point motion segmentation structure drawing of device at big interframe movement video of the embodiment of the invention.This unique point motion segmentation device 100 comprises that feature point extraction module 110, matching characteristic point are to acquisition module 120 and motion segmentation module 130.Feature point extraction module 110 is used for the two adjacent video frames in the big interframe movement video is carried out feature point extraction respectively, and sets up the proper vector of all unique points is described.It is right that matching characteristic point is used for the matching characteristic point that obtains between the described two adjacent video frames according to described unique point and characteristic of correspondence vector description to acquisition module 120.Motion segmentation module 130 is used for according to the plane homograph, utilizes the method for ballot to carry out cutting apart of unique point motion.
The method of use characteristic point coupling of the present invention is asked for motion, in consecutive frame, carry out the feature point extraction second time, afterwards the unique point of two interframe is carried out characteristic matching,, thereby realized the foundation of the unique point motion of big interframe movement video with the motion of the coordinate difference characteristic feature of matching characteristic point.
The unique point classification of motions method that the present invention proposes is utilized the plane homograph, and good portrayal has been carried out in the motion of planar object in the scene or almost plane object, makes the classification of motions of unique point on this type objects has been obtained good effect.Simultaneously, unique point classification of motions method of the present invention can realize the automatic removal of error characteristic point motion has been improved the robustness that algorithm is asked for wrong motion effectively.
Although illustrated and described embodiments of the invention, for the ordinary skill in the art, be appreciated that without departing from the principles and spirit of the present invention and can carry out multiple variation, modification, replacement and modification that scope of the present invention is by claims and be equal to and limit to these embodiment.
Claims (9)
1. the unique point motion segmentation method at big interframe movement video is characterized in that, may further comprise the steps:
Two adjacent video frames in the big interframe movement video is carried out feature point extraction respectively, and set up the proper vector of all unique points is described;
Right according to the matching characteristic point that described unique point and characteristic of correspondence vector description obtain between the described two adjacent video frames; With
According to the plane homograph, utilize the method for ballot to carry out cutting apart of unique point motion.
2. the method for claim 1 is characterized in that, describedly obtains matching characteristic point between the described two adjacent video frames to further comprising according to unique point and characteristic of correspondence vector description:
Set up in the described two adjacent video frames frame respectively with respect to the candidate matches unique point of another frame;
If two unique points candidate matches unique point of the other side each other in the described two adjacent video frames, then these two unique points are exactly that matching characteristic point is right.
3. method as claimed in claim 2 is characterized in that, described unique point is the SIFT unique point.
4. the method for claim 1 is characterized in that, described method according to plane homograph utilization ballot carries out comprising cutting apart further of unique point motion:
Obtain the initial plane homograph according to the part matching characteristic point that reasonably extracts from matching characteristic point centering;
Vote according to all initial plane homographs of all matching characteristic point subtends, remove wrong plane homograph according to voting results, the plane homograph that merges the expression same movement, and with correct matching characteristic point to distributing to corresponding plane homograph, wherein, the matching characteristic point that comprises of each plane homograph is to representing of a sort unique point motion.
5. method as claimed in claim 4 is characterized in that, wherein, judges according to following formula a unique point satisfies an initial plane homograph to whether:
6. the unique point motion segmentation device at big interframe movement video is characterized in that, comprising:
The feature point extraction module is used for the two adjacent video frames in the big interframe movement video is carried out feature point extraction respectively, and sets up the proper vector of all unique points is described;
Matching characteristic point is to acquisition module, and it is right to be used for the matching characteristic point that obtains between the described two adjacent video frames according to described unique point and characteristic of correspondence vector description; With
The motion segmentation module is used for according to the plane homograph, utilizes the method for ballot to carry out cutting apart of unique point motion.
7. device as claimed in claim 6 is characterized in that, described unique point is the SIFT unique point.
8. device as claimed in claim 6, it is characterized in that, described motion segmentation module obtains the initial plane homograph according to the part matching characteristic point that reasonably extracts from matching characteristic point centering, and vote according to all initial plane homographs of all matching characteristic point subtends, remove wrong plane homograph according to voting results, the plane homograph that merges the expression same movement, and with correct matching characteristic point to distributing to corresponding plane homograph, wherein, the matching characteristic point that comprises of each plane homograph is to representing of a sort unique point motion.
9. device as claimed in claim 8 is characterized in that, wherein, judges according to following formula a unique point satisfies an initial plane homograph to whether:
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| CN109708632A (en) * | 2019-01-31 | 2019-05-03 | 济南大学 | A kind of laser radar towards mobile robot/INS/ terrestrial reference pine combination navigation system and method |
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