Real-time Scene Recognition on Embedded System with SIFT Keypoints and a New Descriptor

	Real-time Scene Recognition on Embedded System with SIFT Keypoints and a New Descriptor
	Xiao, Han; He, Wenhao; Yuan, Kui; Wen, Feng
	2013-08
会议名称	2013 IEEE International Conference on Mechatronics and Automation
会议录名称	2013 IEEE International Conference on Mechatronics and Automation
会议日期	Aug. 4-7, 2013
会议地点	Takamatsu, Japan
摘要	The vision system of a mobile robot has to interpret the environment in real time at low power. As a good algorithm for extracting information from images, SIFT (Scale Invariant Feature Transform) is widely used in computer vision. However, the high computational complexity makes it hard to achieve real-time performance of SIFT with pure software. This paper presents a machine vision system implementing the SIFT algorithm on an embedded image processing card, where real-time scene recognition is accomplished with low power consumption through the cooperation between an FPGA (Field Programmable Gate Array) and a DSP (Digital Signal Processor) chip. The original SIFT keypoint detection algorithm is adapted for parallel computation and implemented with a hardware pipeline in the FPGA. Although our current system is designed for 360x288 video frames, this pipelined architecture can be applied to images with arbitrary resolution. Meanwhile, the original 128-dimensional SIFT descriptor is replaced by an 18-dimensional new descriptor which can be generated more efficiently and can be matched according to an absolute distance threshold with the distance defined by infinity-norm. On this basis, a five-branch-tree data structure is designed for fast searching and matching of descriptors, and robust scene recognition is realized through the combination of keypoints. Since our new descriptor allows one keypoint to be matched to several keypoints, which is a distinct property from the original SIFT algorithm, our system can recognize multiple images with overlapping contents simultaneously. In addition, compared with traditional work that needs off-line training, our system can perform fast on-line learning, which is a desirable property for mobile robots.
关键词	Fpga Sift Descriptor Image Recognition Real-time
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12134
专题	智能制造技术与系统研究中心_智能机器人
通讯作者	Xiao, Han
作者单位	Institute of Automation, Chinese Academy of Sciences
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Xiao, Han,He, Wenhao,Yuan, Kui,et al. Real-time Scene Recognition on Embedded System with SIFT Keypoints and a New Descriptor[C],2013.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
2013_Real-time Scene（2200KB）	会议论文		开放获取	CC BY-NC-SA	浏览下载