DocumentCode :
590697
Title :
SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video
Author :
Suzuki, Takumi ; Ikenaga, Takeshi
Author_Institution :
Waseda Univ., Tokyo, Japan
fYear :
2012
fDate :
3-6 Dec. 2012
Firstpage :
1
Lastpage :
6
Abstract :
Scale-Invariant Feature Transform (SIFT) has lately attracted attention in computer vision as a robust keypoint detection algorithm which is invariant for scale, rotation and illumination change. However, its computational complexity is too high to apply practical real-time applications. This paper proposes a low complexity keypoint extraction algorithm based on SIFT descriptor and utilization of the database, and its real-time hardware implementation for Full-HD resolution video. The proposed algorithm computes SIFT descriptor on the keypoint obtained by corner detection and selects a scale from the database. It is possible to parallelize the keypoint detection and descriptor computation modules in the hardware. These modules do not depend on each other in the proposed algorithm in contrast with SIFT that computes a scale. The processing time of descriptor computation in this hardware is independent of the number of keypoints because its descriptor generation is pipelining structure of pixel. Evaluation results show that the proposed algorithm on software is 12 times faster than SIFT. Moreover, the proposed hardware on FPGA is 427 times faster than SIFT and 61 times faster than the proposed algorithm on software. The proposed hardware performs keypoint extraction and matching at 60 fps for Full-HD video.
Keywords :
computational complexity; computer vision; feature extraction; field programmable gate arrays; image resolution; object detection; video signal processing; FPGA; SIFT descriptor; SIFT-based low complexity keypoint extraction algorithm; computation modules; computational complexity; computer vision; corner detection; descriptor generation; full-HD resolution video; keypoint detection; pipelining structure; real-time hardware implementation; robust keypoint detection algorithm; scale-invariant feature transform; Approximation methods; Complexity theory; Databases; Hardware; Pipeline processing; Software; Software algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific
Conference_Location :
Hollywood, CA
Print_ISBN :
978-1-4673-4863-8
Type :
conf
Filename :
6411844
Link To Document :
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