Pedestrian Detection Based on Multi-Block Local Binary Pattern and Biologically Inspired Feature

Aminou Halidou, Xinge You, Bachirou Bogno


Nowadays pedestrian detection plays an important role in security and driving assistance. Detecting moving object is complex, and some of the detection methods are comparatively ineffective and slow.  In relation to human detection it is very useful to combine independent information sources, such as appearance and motion. To achieve acceptable detection performance, we propose inter-frames differencing image to compute the region of interest, and MB-BIF to extract features. The MB-BIF approach combines two well-known methods, the Multi-Block Local Binary Pattern and Biologically Inspired Method.  We evaluate the performance of different features descriptors on different databases, and our method shows good efficiency.

Full Text:



Computer and Information Science   ISSN 1913-8989 (Print)   ISSN 1913-8997 (Online)
Copyright © Canadian Center of Science and Education

To make sure that you can receive messages from us, please add the '' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.