Estimation of depth fields suitable for video compression based on 3-D structure and motion of objects
Date
1998-06Source Title
IEEE Transactions on Image Processing
Print ISSN
1057-7149
Publisher
Institute of Electrical and Electronics Engineers
Volume
7
Issue
6
Pages
904 - 908
Language
English
Type
ArticleItem Usage Stats
205
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198
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Abstract
Intensity prediction along motion trajectories removes temporal redundancy considerably in video compression algorithms. In three-dimensional (3-D) object-based video coding, both 3-D motion and depth values are required for temporal prediction. The required 3-D motion parameters for each object are found by the correspondence-based E-matrix method. The estimation of the correspondences - two-dimensional (2-D) motion field - between the frames and segmentation of the scene into objects are achieved simultaneously by minimizing a Gibbs energy. The depth field is estimated by jointly minimizing a defined distortion and bitrate criterion using the 3-D motion parameters. The resulting depth field is efficient in the rate-distortion sense. Bit-rate values corresponding to the lossless encoding of the resultant depth fields are obtained using predictive coding; prediction errors are encoded by a Lempel-Ziv algorithm. The results are satisfactory for real-life video scenes.
Keywords
3-D motion3-D structure
Dense depth estimation
Depth encoding
Motion analysis
Object-based video coding
Rate-distortion theory
Algorithms
Gibbs free energy
Image analysis
Image coding
Image quality
Image segmentation
Matrix algebra
Object recognition
Signal distortion
Three dimensional computer graphics
Dense depth estimation
Rate distortion theory
Image compression