On real-time multi-view video coding using parallel processing of sparse representation

2014 Fiscal Year Final Research Report

• Project/Area Number: 24500231
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Perception information processing/Intelligent robotics
• Research Institution: Kurume National College of Technology
• Principal Investigator: KUROKI Yoshimitsu 久留米工業高等専門学校, 制御情報工学科, 准教授 (60290847)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 画像符号化 / スパース表現 / GPGPU / 多視点画像

Outline of Final Research Achievements

Sparse representation is one of the hottest topics in signal processing, and approximates a given signal by a linear combination of less numbers of basis vectors. In this research, we applied sparse representation to multi-view video coding to achieve higher coding performance than the conventional video coding framework used in MPEGs, and tried faster implementation using multi-cores in GPU and CPU. Research results show the effectiveness of sparse representation in video coding, and also tell us that the proposed parallel processing is about 2.7 times faster than the execution using CPU. This research includes accurate estimation of Fundamental matrix to obtain geometric information of objects from multi-view images.

Free Research Field

知覚情報処理