Object boundary detection using a constrained viterbi search

Details Object boundary detection using a constrained viterbi search Object boundary detection using a constrained viterbi search

1998-12-22

2001-07-24

Johns, Andrew W. (Department: 2621)

Image analysis

Pattern recognition

Feature extraction

Reexamination Certificate

active

06266443

ABSTRACT:

FIELD OF THE INVENTION
This invention relates generally to boundary detection, and more particularly, to segmenting objects in a video sequence to obtain video object planes.
BACKGROUND OF THE INVENTION
Older video standards, such as ISO MPEG- 1 and MPEG-2, are relatively low-level specifications primarily dealing with the temporal and spatial compression of video signals. With these standards, one can achieve high compression ratios over a wide range of applications.
Newer video coding standards, such as MPEG-4, see “Information Technology—Generic coding of audio/visual objects,” ISO/IEC FDIS 14496-2 (MPEG4 Visual), November 1998, allow arbitrary-shaped objects to be encoded and decoded as separate video object planes (VOP's). These emerging standards are intended to enable multimedia applications, such as interactive video, where natural and synthetic materials are integrated, and where access is universal. For example, one might want to “cut-and-paste” a moving figure from one video to another. In order to identify the figure, the video must first be “segmented.” Given the amount of video, both archived and newly acquired, it is desirable for the segmentation process to be either fully automatic or semi-automatic.
In the semi-automatic case, one may provide a segmentation for the first frame. The problem then becomes one of object tracking. In the automatic case, the problem is to first identify the object, then to track the object. In either case, the segmentation process should attempt to minimize the input needed by the user, obviously, no input is optimal.
With VOP's, each frame of a video sequence is segmented into arbitrarily shaped image regions. Each VOP describes a video object in terms of, for example, shape, motion, and texture. The exact method of producing VOP's from the source imagery is not defined by the standards. It is assumed that “natural” objects are represented by shape information, in addition to the usual luminance and chrominance components. Shape data can be provided as a segmentation mask, or as a gray scale alpha plane to represent multiple overlaid objects. Because video objects vary extensively with respect to low-level features, such as, optical flow, color, and intensity, VOP segmentation is a very difficult problem.
A number of segmentation methods are known. Region-based segmentation methods include mesh-based, motion model-based, and split-and-merge. Because these methods rely on spatial features, such as luminance, they may produce false contours, and in some cases, foreground objects may be merged into the background. More recently, morphological spatio-temporal segmentation has been used. There, information from both the spatial (luminance) and temporal (motion) domains are tracked using vectors. This complex method might erroneously assign a spatial region to a temporal region, and the method is difficult to apply to a video sequence including more than one object.
SUMMARY OF THE INVENTION
A search method detects object boundaries in a sequence of two-dimensional images. In the sequence, each image has multiple intensity value points. Filtering and motion analysis are applied on each image to produce motion enhanced images. Initial search parameters are determined from a dynamic snake model applied to the motion enhanced images.
Each motion enhanced image is searched for a potential boundary using the search parameters. In one aspect of the event, the search is performed by a constrained Viterbi method. The potential boundary is projected into the motion enhanced image of a previous, current, and next image, and the search parameters of the previous, current, and next images are updated. The searching, projecting, and updating repeat until a predetermined level of convergence is reached.


REFERENCES:
patent: 4959714 (1990-09-01), Lo et al.
patent: 5103488 (1992-04-01), Gemello et al.
patent: 5974521 (1999-10-01), Akerib
patent: 6002722 (1999-12-01), Wu
patent: 0817495 A2 (1998-01-01), None
Dimitriadis et al.; “Boundary Detection in Images Using a Two-Component Model”; Proceeding of the Mediterranean Electrotechnical Conference; 1983, pp. 1-2.

Affiliated with

Also associated with

Rating

Object boundary detection using a constrained viterbi search does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Object boundary detection using a constrained viterbi search, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Object boundary detection using a constrained viterbi search will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-2436331