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10 January 1997 Motion-field and image-intensity segmentation for object-oriented coding of video sequences
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Proceedings Volume 3024, Visual Communications and Image Processing '97; (1997)
Event: Electronic Imaging '97, 1997, San Jose, CA, United States
A number of object-oriented coding algorithms have been proposed for coding video sequences at low bit rates. Instead of estimating motion of pixel blocks, these algorithms segment each image into regions of uniform motion and estimate the motion of these regions. Estimating the segmentation and computing motion parameters are evidently closely related. Most algorithms iteratively compute complex motion parameters and segmentation estimates, and typically computationally intensive. Image intensity segmentations were also used instead of motion field segmentations based on the hypothesis that adjacent pixels with similar luminance values are part of the same object, and therefore share common motion parameters. We previously proposed a simple tow-stage algorithm for which 1) a translational block-motion field is used to compute a translational motion field and its segmentation, 2) an optical flow field is then used to compute affine motion parameters for each segmented region. In this paper, we propose to replace the translational block motion field by another translational motion field which assigns a motion vector to each region of an image intensity segmentation. This approach combines the advantages of both intensity and motion filed segmentations, generates motion field segmentations that matches the scene content more closely with 15 percent-25 percent fewer objects, and therefore reduces the side bit rate required for coding the motion field segmentation.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dam LeQuang and Andre Zaccarin "Motion-field and image-intensity segmentation for object-oriented coding of video sequences", Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997);

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