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Real-time SIFT-based Object Recognition System
Wang, Zhao; Xiao, Han; He, Wenhao; Wen, Feng; Yuan, Kui
2013-08
Conference Name2013 IEEE International Conference on Mechatronics and Automation
Source Publication2013 IEEE International Conference on Mechatronics and Automation
Conference DateAug, 4-7, 2013
Conference PlaceTakamatsu, Japan
Abstract
In this paper a real-time object recognition system is realized, based on the Scale Invariant Feature Transform (SIFT) algorithm. The system mainly contains a display, a camera and an image acquisition and processing board developed by our research team. An FPGA chip and a DSP chip are embedded in the card as the major calculation units, which make real-time computation possible. The whole recognition algorithm is divided into three parts: the detection of SIFT keypoints, the extraction of SIFT descriptors and the final object recognition. In order to achieve real-time detection of SIFT keypoints through hardware computation on FPGA, the original SIFT algorithm is adapted to accommodate the parallel computation and pipelined structure of hardware. Using a mode of DSP invoking a customized FPGA module, a 72-dimensional keypoint descriptor is proposed to save memory space and to cut down the computing cost in keypoints matching. The recognition proceeds by matching individual features to a database of features from known objects using a fast approximate nearestneighbor search algorithm changed based on the k-d tree and the BBF algorithm. In addition, three matching strategies are adopted to discard the false matches so as to improve the accuracy of recognition. The object recognition functionality is mainly achieved in the DSP. A model database is built and used to test the accuracy and effectiveness of the system.
KeywordObject Recognition Sift Keypoints Embedded System K-d Tree Bbf Algorithm
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12135
Collection智能制造技术与系统研究中心_智能机器人
Corresponding AuthorWang, Zhao
AffiliationInstitute of Automation, Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Zhao,Xiao, Han,He, Wenhao,et al. Real-time SIFT-based Object Recognition System[C],2013.
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