Estimation of depth fields suitable for video compression using 3-D structures and motion of objects

Cataloged from PDF version of article.Intensity prediction along motion trajectories removes temporal redundancy considerably in video compression algorithms. In threedimensional (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 Ematrix 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

Object-based video representations: shape compression and object segmentation

Object-based video representations are considered to be useful for easing the process of multimedia content production and enhancing user interactivity in multimedia productions. Object-based video presents several new technical challenges, however. Firstly, as with conventional video representations, compression of the video data is a requirement. For object-based representations, it is necessary to compress the shape of each video object as it moves in time. This amounts to the compression of moving binary images. This is achieved by the use of a technique called context-based arithmetic encoding. The technique is utilised by applying it to rectangular pixel blocks and as such it is consistent with the standard tools of video compression. The blockbased application also facilitates well the exploitation of temporal redundancy in the sequence of binary shapes. For the first time, context-based arithmetic encoding is used in conjunction with motion compensation to provide inter-frame compression. The method, described in this thesis, has been thoroughly tested throughout the MPEG-4 core experiment process and due to favourable results, it has been adopted as part of the MPEG-4 video standard. The second challenge lies in the acquisition of the video objects. Under normal conditions, a video sequence is captured as a sequence of frames and there is no inherent information about what objects are in the sequence, not to mention information relating to the shape of each object. Some means for segmenting semantic objects from general video sequences is required. For this purpose, several image analysis tools may be of help and in particular, it is believed that video object tracking algorithms will be important. A new tracking algorithm is developed based on piecewise polynomial motion representations and statistical estimation tools, e.g. the expectationmaximisation method and the minimum description length principle

Prediction of image partitions using Fourier descriptors: application to segmentation-based coding schemes

This paper presents a prediction technique for partition sequences. It uses a region-by-region approach that consists of four steps: region parameterization, region prediction, region ordering, and partition creation. The time evolution of each region is divided into two types: regular motion and shape deformation. Both types of evolution are parameterized by means of the Fourier descriptors and they are separately predicted in the Fourier domain. The final predicted partition is built from the ordered combination of the predicted regions, using morphological tools. With this prediction technique, two different applications are addressed in the context of segmentation-based coding approaches. Noncausal partition prediction is applied to partition interpolation, and examples using complete partitions are presented. In turn, causal partition prediction is applied to partition extrapolation for coding purposes, and examples using complete partitions as well as sequences of binary images-shape information in video object planes (VOPs)-are presented.Peer ReviewedPostprint (published version

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio