Title: Algorithm and Architecture of Disparity Estimation With Mini-Census Adaptive Support Weight
Authors: Chang, Nelson Yen-Chung
Tsai, Tsung-Hsien
Hsu, Bo-Hsiung
Chen, Yi-Chun
Chang, Tian-Sheuan
Department of Electronics Engineering and Institute of Electronics
Keywords: Application-specific integrated circuits (ASIC);computer vision;digital circuits;digital integrated circuits;very large scale integration (VLSI)
Issue Date: 1-Jun-2010
Abstract: High-performance real-time stereo vision system is crucial to various stereo vision applications, such as robotics, autonomous vehicles, multiview video coding, freeview TV, and 3-D video conferencing. In this paper, we proposed a high-performance hardware-friendly disparity estimation algorithm called mini-census adaptive support weight (MCADSW) and also proposed its corresponding real-time very large scale integration (VLSI) architecture. To make the proposed MCADSW algorithm hardware-friendly, we proposed simplification techniques such as using mini-census, removing proximity weight, using YUV color representation, using Manhattan color distance, and using scaled-and-truncate weight approximation. After applied these simplifications, the MCADSW algorithm was not only hardware-friendly, but was also 1.63 times faster. In the corresponding realtime VLSI architecture, we proposed partial column reuse and access reduction with expanded window to significantly reduce the bandwidth requirement. The proposed architecture was implemented using United Microelectronics Corporation (UMC) 90 nm complementary metal-oxide-semiconductor technology and can achieve a disparity estimation frame rate of 42 frames/s for common intermediate format size images when clocked at 95 MHz. The synthesized gate-count and memory size is 563k and 21.3 kB, respectively.
URI: http://dx.doi.org/10.1109/TCSVT.2010.2045814
ISSN: 1051-8215
DOI: 10.1109/TCSVT.2010.2045814
Volume: 20
Issue: 6
Begin Page: 792
End Page: 805
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