A Multiplication-Free Algorithm and A Parallel Architecture for Affine Transformation
Journal of VLSI Signal Processing Systems
Mosaic based representations of video sequences and their applications
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Unsupervised object-based sprite coding system for tennis sport
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Fast and robust parameter estimation method for global motion compensation in the video coder
IEEE Transactions on Consumer Electronics
Digital image stabilization with sub-image phase correlation based global motion estimation
IEEE Transactions on Consumer Electronics
Efficient, robust, and fast global motion estimation for video coding
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Multicore system-on-chip architecture for MPEG-4 streaming video
IEEE Transactions on Circuits and Systems for Video Technology
Fast gradient methods based on global motion estimation for video compression
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Integration of Digital Stabilizer With Video Codec for Digital Video Cameras
IEEE Transactions on Circuits and Systems for Video Technology
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Global motion estimation and compensation (GME/GMC) is an important video processing technique and has been applied to many applications including video segmentation, sprite/mosaic generation, and video coding. In MPEG-4 Advanced Simple Profile (ASP), GME/GMC is adopted to compensate camera motions. Since GME is important, many GME algorithms have been proposed. These algorithms have two common characteristics, huge computation complexity and ultra large memory bandwidth. Hence for realtime applications, a hardware accelerator of GME is required. However, there are many hardware design challenges of GME like irregular memory access and huge memory bandwidth, and only few hardware architectures have been proposed. In this paper, we first analyzed three typical algorithms of GME, and a fast GME algorithm is proposed. By using temporal prediction and skipping the redundant computation, 91% memory bandwidth and 80% iterations are saved, while the performance is kept, compared to Gradient Descent in MPEG-4 Verification Model. Based on our proposed algorithm, a hardware architecture of GME is also presented. A new scheduling, Reference-Based Scheduling, is developed to solve the irregular memory access problem. An interleaved memory arrangement is applied to satisfy the memory access requirement of interpolation. The total gate count of hardware implementation is 131 K with Artisan 0.18 um cell library, and the internal memory size is about 7.9 Kb. Its processing ability is MPEG-4 ASP@L3, which is 352脳288 with 30 fps, at 30 MHz.