SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video

Takahiro Suzuki, Takeshi Ikenaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
Publication statusPublished - 2012
Event2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 - Hollywood, CA
Duration: 2012 Dec 32012 Dec 6

Other

Other2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
CityHollywood, CA
Period12/12/312/12/6

Fingerprint

Mathematical transformations
Hardware
Computer vision
Field programmable gate arrays (FPGA)
Computational complexity
Lighting
Pixels
Processing

ASJC Scopus subject areas

  • Information Systems

Cite this

Suzuki, T., & Ikenaga, T. (2012). SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video. In 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 [6411844]

SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video. / Suzuki, Takahiro; Ikenaga, Takeshi.

2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012. 2012. 6411844.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suzuki, T & Ikenaga, T 2012, SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video. in 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012., 6411844, 2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012, Hollywood, CA, 12/12/3.
Suzuki T, Ikenaga T. SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video. In 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012. 2012. 6411844
Suzuki, Takahiro ; Ikenaga, Takeshi. / SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video. 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012. 2012.
@inproceedings{f59ca7b070c5415d8fa19cac74bd8d34,
title = "SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video",
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.",
author = "Takahiro Suzuki and Takeshi Ikenaga",
year = "2012",
language = "English",
isbn = "9780615700502",
booktitle = "2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012",

}

TY - GEN

T1 - SIFT-based low complexity keypoint extraction and its real-time hardware implementation for full-HD video

AU - Suzuki, Takahiro

AU - Ikenaga, Takeshi

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84874399674&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84874399674&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9780615700502

BT - 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012

ER -