Object-based Video Compression Research Articles

A New Object-Based System for Fractal Video Sequences Compression

A novel object-based fractal monocular and stereo video compression scheme with quadtree-based motion and disparity compensation is proposed in this paper. Fractal coding is adopted and each object is encoded independently by a prior image segmentation alpha plane, which is defined exactly as in MPEG-4. The first n frames of right video sequence are encoded by using the Circular Prediction Mapping (CPM) and the remaining frames are encoded by using the Non Contractive Interframe Mapping (NCIM). The CPM and NCIM methods accomplish the motion estimation/ compensation of right video sequence. According to the different coding or user requirements, the spatial correlations between the left and right frames can be explored by partial or full affine transformation quadtree-based disparity estimation/ compensation, or simply by applying CPM/NCIM on left video sequence. The testing results with the nature monocular and stereo video sequences provide promising performances at low bit rate coding. We believe it will be a powerful and efficient technique for the object-based monocular and stereo video sequences coding.

Codificação de Cadeia Eficientes para Compactação da Informação de Forma em Compressão de Vídeo Baseada em Objetos

In applications of object-based video compression, one of the most efficient strategies for lossless coding of object shapes is the differential chain coder (DCC). In this paper, several modifications of a DCC are identified and analyzed with the purpose of improving its efficiency. The number of spatial prediction classes in a conditional DCC was increased. In addition, we explored in a more effective and integrated form, the spatial and temporal correlations between pixels of the object contour. As compared to the methods available in the literature, the modifications that provided the highest compaction of the shape information were incorporated to the three schemes proposed in this paper: the adaptive conditional DCC, the DCC conditioned to the current frame and the DCC conditioned to the previous frame. In all cases, we have also considered the effects of different choices for the table of the Huffman codes, over the final compression rate.

A survey on the techniques for the transport of MPEG-4 video over wireless networks

In this paper, we present a survey on the techniques for the transport of MPEG-4 video over wireless networks. As a new object-based video compression standard, MPEG-4 has been proved to be suitable for wireless applications. However, because of the characteristics of wireless channels, such as varying channel capacity and burst bit errors, some new techniques such as scalable and error-resilient video coding techniques are required to be incorporated into MPEG-4 to improve the coding efficiency. These techniques are discussed in this paper. The experimental results show that although these new techniques have improved the performance greatly, there is still a lot of research work to be pursued.

Object-based video coding by global-to-local motion segmentation

We describe an object-based video compression scheme based on the derivation and efficient coding of motion boundaries. First, we recursively identify a small number of global movement classes, each represented by two or more motion parameters. Second, we assign regions of a spatial segmentation to movement classes. Third, we merge segments using various similarity heuristics, while adding movement classes for small objects, if necessary. Finally, the boundaries of motion are coded using an efficient asymmetric binary tree coding scheme. Experimental results on standard test sequences qualitatively show that the proposed algorithm gives good segmentation, and that it is suitable for very-low-data-rate object-based coding.

Hierarchical 2-D mesh representation, tracking, and compression for object-based video

This paper proposes methods for designing, tracking and coding hierarchical two-dimensional (2-D) content-based mesh representations. The design procedure consists of constructing a fine-to-coarse hierarchy of Delaunay meshes, using image- and shape-based criteria for mesh geometry simplification. Hierarchical tracking employs a coarse-to-fine strategy with mesh-based motion vector optimization. We introduce new techniques to maintain the initial mesh hierarchy and topology during tracking by imposing certain constraints at each stage of the procedure. The hierarchical compression technique is based on a nearest neighbor ordering of mesh node points. This ordering serves to identify the mesh boundary nodes as well as establish spatial predictors for differential coding of node coordinates and motion vectors. The proposed hierarchical mesh representation, which has applications in object-based video manipulation, investing, and compression, provides improved tracking performance (compared to a nonhierarchical representation) and allows progressive (scalable) transmission of the object geometry (including shape) and motion information, as well as variable level-of-detail rendering. Experimental results are presented to compare the tracking and compression performance of hierarchical versus nonhierarchical mesh representations and to demonstrate the tradeoff between image quality and mesh bit rate for 2-D mesh-based video object rendering.

A perturbation analysis and performance bound for the estimation of 3-D camera translation direction

The estimation of the 3-D displacement of a moving camera relative to a scene is critical for applications in robotics as well as object-based video compression. By estimating the relative motion within a scene, one can accurately predict object positions for the future, thereby reducing the amount of information which must be coded. This problem has an inherently nonlinear nature and can therefore be computationally expensive. However, several related linear methods which use optical flow to recover the translation direction of a moving camera have been previously presented. These algorithms all depend on solving a constrained least-squares minimization problem. In this paper, we investigate the effects of noise perturbations on eigenvector and eigenvalue estimates for least-squares solutions, including a necessary modification to the Cramér-Rao lower bound (CRLB), which specifies the minimum possible covariance matrix for constrained estimators. We propose a computationally simple nonlinear algorithm which produces near-optimal translation-direction estimates (in the sense that the mean vector is unbiased and the covariance matrix approaches the CRLB). Sample numerical results are used to compare the various techniques and illustrate the agreement between predicted and observed values. Finally, some remaining problems meriting further investigation are discussed.

Trifocal motion modeling for object-based video compression and manipulation

Following an overview of two-dimensional (2-D) parametric motion models commonly used in video manipulation and compression, we introduce trifocal transfer, which is an image-based scene representation used in computer vision, as a motion compensation method that uses three frames at a time to implicitly capture camera/scene motion and scene depth. Trifocal transfer requires a trifocal tensor that is computed by matching image features across three views and a dense correspondence between two of the three views. We propose approximating the dense correspondence between two of the three views by a parametric model in order to apply the trifocal transfer for object-based video compression and background mosaic generation. Backward, forward, and bidirectional motion compensation methods based on trifocal transfer are presented. The performance of the proposed motion compensation approaches using the trifocal model has been compared with various other compensation methods, such as dense motion, block motion, and global affine transform on several video sequences. Finally, video compression and mosaic synthesis based on the trifocal motion model are implemented within the MPEG-4 Video Verification Model (VM), and the results are compared with those of the standard MPEG-4 video VM. Experimental results show that the trifocal motion model is superior to block and affine models when there is depth variation and camera translation.

Two- versus three-dimensional object-based video compression

This paper compares two-dimensional (2-D) and three-dimensional (3-D) object modeling in terms of their capabilities and performance (peak signal-to-noise-ratio and visual image quality) for very low bitrate video coding. We show that 2-D object-based coding with affine/perspective transformations and triangular mesh models can simulate almost all capabilities of 3-D object-based approaches using wireframe models at a fraction of the computational cost. Furthermore, experiments indicate that a 2-D mesh-based coder-decoder performs favorably compared to the new H.263 standard in terms of visual quality.

A robust, scalable, object-based video compression technique for very low bit-rate coding

This paper describes an object-based video coding scheme (OBVC) that was proposed by Texas Instruments to the emerging ISO MPEG-4 video compression standardization effort. This technique achieves efficient compression by separating coherently moving objects from stationary background and compactly representing their shape, motion, and the content. In addition to providing improved coding efficiency at very low bit rates, the technique provides the ability to selectively encode, decode, and manipulate individual objects in a video stream. This technique supports all three MPEG-4 functionalities tested in the November 1995 tests, namely, improved coding efficiency, error resilience, and content scalability. This paper also describes the error protection and concealment schemes that enable robust transmission of compressed video over noisy communication channels such as analog phone lines and wireless links. The noise introduced by the communication channel is characterized by both burst errors and random bit errors. Applications of this object-based video coding technology include videoconferencing, video telephony, desktop multimedia, and surveillance video.