Rapid and precise object detection based on color histograms and adaptive bandwidth mean shift

Authors:
Xiaopeng Chen;Qiang Huang;Peng Hu;Min Li;Ye Tian;Chen Li
Affiliations:
School of Mechatronics, Beijing Institute of Technology, Beijing, China;School of Mechatronics, Beijing Institute of Technology, Beijing, China;Hitech Innovation Center, Chinese Academy of Sciences, Beijing, China;School of Mechatronics, Beijing Institute of Technology, Beijing, China;School of Mechatronics, Beijing Institute of Technology, Beijing, China;School of Mechatronics, Beijing Institute of Technology, Beijing, China
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

Speed and precision are important for object detection algorithms. In this paper, a novel object detection algorithm based on color histogram and adaptive bandwidth mean shift is proposed. The algorithm is capable of detecting objects rapidly and precisely. It is composed of two stages: a rough detection stage and a precise detection stage. At the rough detection stage, histogram back projection and thresholding are applied to fast object identification and rough global localization. At the precise detection stage, the precise position, size and orientation are derived under the adaptive bandwidth mean shift framework. Experiments verify that the algorithm is able to detect the size, position and orientation of general objects rapidly and precisely.