Fast pedestrian detection based on multiple instance hierarchical HOG matrices

Guang Cheng; Long Meng; Xinggang Lin

doi:10.1117/12.2034377

19 December 2013 Fast pedestrian detection based on multiple instance hierarchical HOG matrices

Guang Cheng, Long Meng, Xinggang Lin

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 90450G (2013) https://doi.org/10.1117/12.2034377
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

Abstract

Many pedestrian detection research works focused on the improvement of detection performance, without considering the detection speed, making the detection algorithms not applicable for real-world requirement for real-time processing. To explore this problem, we first propose a pre-processing method Hierarchical HOG Matrices to replace the traditional integral histogram of gradients, which stores more data in the pre-processing phase to reduce computation time. A matrix-based detection computation structure is also proposed, which organize the massive data computations in the scanning detection process into matrix operations to optimize the overall speed. We then add multiple instance learning into the fast pedestrian detection algorithm to further enhance its accuracy. Experiments demonstrate that the proposed fast and robust pedestrian detection algorithm based on the multiple instance feature achieves an accuracy comparable to the latest algorithms, with the best speed among the algorithms with an accuracy of the same level.

Citation Download Citation

Guang Cheng, Long Meng, and Xinggang Lin "Fast pedestrian detection based on multiple instance hierarchical HOG matrices", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 90450G (19 December 2013); https://doi.org/10.1117/12.2034377

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Detection and tracking algorithms

Matrices

Sensors

Image processing

Data storage

Algorithm development

Feature extraction

Show All Keywords

Keywords/Phrases

Search In:

Publication Years