Model-Based Power Aware Compression Algorithms for MPEG-4 Virtual Human Animation in Mobile Environments

Abstract

Abstract-MPEG-4 body animation parameters (BAP) are used for animation of MPEG-4 compliant virtual human-like characters. Distributed virtual reality applications and networked games on mobile computers require access to locally stored or streamed compressed BAP data. Existing MPEG-4 BAP compression techniques are inefficient for streaming, or storing, BAP data on mobile computers, because: 1) MPEG-4 compressed BAP data entails a significant number of CPU cycles, hence significant, unacceptable power consumption, for the purpose of decompression; 2) the lossy MPEG-4 technique of frame dropping to reduce network throughput during streaming leads to unacceptable animation degradation; and 3) lossy MPEG-4 compression does not exploit structural information in the virtual human model. In this article, we propose two novel algorithms for lossy compression of BAP data, termed as BAP-Indexing and BAP-Sparsing. We demonstrate how an efficient combination of the two algorithms results in a lower network bandwidth requirement and reduced power for data decompression at the client end when compared to MPEG-4 compression. The algorithm exploits the structural information in the virtual human model, thus maintaining visually acceptable quality of the resulting animation upon decompression. Consequently, the hybrid algorithm for BAP data compression is ideal for streaming of motion animation data to power-and network-constrained mobile computers.

Virtual character animation mapping

“…Table. I presents the compression simulation of 12 motion data for lossless compression in the image domain. In the experiment, the VCA mapping technique is able to achieve an average of 7.363 compression ratio against the original AMC file without significant degradation in the reconstructed motion quality outperforming the existing technique proposed in [2] reporting an average of 1.7-2.5 compression rate for varying DEF of 0.17-14. The only quality lost in our process is due to the double to integer casting during the image mapping stage.…”

“…The displacement error per frame DEF proposed in [2] is used for this purpose. We define the resulting motion data of all joints from the decoded DOF as J where J(t) = j 1 , j 2 , ..., j n and j i = {x i , y i , z i }.…”

Progressive transmission of motion capture data for scalable virtual character animation

“…In our experiment, the metric displacement error per frame (DEF) from [1] is used for this purpose. Since the animation quality is usually more dependent on the accuracy of the 3D position than that of the modification angle, thus our evaluation of the DEF is measured respect to the resulting coordinate positions of the avatar's joint from the reconstructed angle modification.…”

Image based representation for 3D content delivery

“…Table 4.1 presents the compression simulation of 12 motion data for lossless compression in the image domain. In the experiment, the VCA mapping technique is able to achieve an average of 7.363 compression ratio against the original AMC file without significant degradation in the reconstructed motion quality outperforming the existing technique proposed in [36] reporting an average of 1.7-2.5 compression ratio for varying DEF of 0.17-14. The only quality lost in our process is due to the double to integer casting during the image mapping stage.…”

“…Skeletal based 3D model has the unique characteristics of both structural and temporal coherency which causes the applications of 3D mesh compression techniques unsuitable, if it is directly applied on the VCA. Previously, [36] proposed the Model based power aware method to achieve efficient compression of the VCA. The structural attributes of the VCA are exploited through the combination of BAP sparsing and indexing techniques.…”