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Stereo-based Robust Human Detection on Pose Variation Using Multiple Oriented 2D Elliptical Filters  

Cho, Sang-Ho (포항공과대학교 컴퓨터공학과)
Kim, Tae-Wan (포항공과대학교 컴퓨터공학과)
Kim, Dae-Jin (포항공과대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.35, no.10, 2008 , pp. 600-607 More about this Journal
Abstract
This paper proposes a robust human detection method irrespective of their pose variation using the multiple oriented 2D elliptical filters (MO2DEFs). The MO2DEFs can detect the humans regardless of their poses unlike existing object oriented scale adaptive filter (OOSAF). To overcome OOSAF's limitation, we introduce the MO2DEFs whose shapes look like the oriented ellipses. We perform human detection by applying four different 2D elliptical filters with specific orientations to the 2D spatial-depth histogram and then by taking the thresholds over the filtered histograms. In addition, we determine the human pose by using convolution results which are computed by using the MO2DEFs. We verify the human candidates by either detecting the face or matching head-shoulder shapes over the estimated rotation. The experimental results showed that the accuracy of pose angle estimation was about 88%, the human detection using the MO2DEFs outperformed that of using the OOSAF by $15{\sim}20%$ especially in case of the posed human.
Keywords
Stereo Image; Human Detection; Multiple Oriented 2D Elliptical Filter; Pose Angle Estimation; Human Verification; Face Detection; Shape Matching;
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