Title
Onboard monocular pedestrian detection by combining spatio-temporal hog with structure from motion algorithm
Abstract
In this paper, we brought out a novel pedestrian detection framework for the advanced driver assistance system of mobile platform under the normal urban street environment. Different from the conventional systems that focus on the pedestrian detection at near distance by interfusing multiple sensors (such as radar, laser and infrared camera), our system has achieved the pedestrian detection at all (near, middle and long) distance on a normally driven vehicle (1---40 km/h) with monocular camera under the street scenes. Since pedestrians typically exhibit not only their human-like shape but also the unique human movements generated by their legs and arms, we use the spatio-temporal histogram of oriented gradient (STHOG) to describe the pedestrian appearance and motion features. The shape and movement of a pedestrian will be described by a unique feature produced by concatenating the spatial and temporal histograms. A STHOG detector trained by the AdaBoost algorithm will be applied to the images stabilized by the structure from motion (SfM) algorithm with geometric ground constraint. The main contributions of this work include: (1) ground constraint with monocular camera to reduce the computational cost and false alarms; (2) preprocessing by stabilizing the successive images captured from mobile camera with the SfM algorithm; (3) long-distance (maximum 100 m) pedestrian detection at various velocities (1---40 km/h). Through the extensive experiments under different city scenes, the effectiveness of our algorithm has been proved.
Year
DOI
Venue
2015
10.1007/s00138-014-0653-y
Machine Vision and Applications
Keywords
Field
DocType
Spatio-temporal HOG,Pedestrian detection,Onboard monocular camera,Structure from motion
Structure from motion,Histogram,Pedestrian,Computer science,Artificial intelligence,Monocular,Detector,Pedestrian detection,Radar,Computer vision,Pattern recognition,Algorithm,Preprocessor
Journal
Volume
Issue
ISSN
26
2-3
0932-8092
Citations 
PageRank 
References 
2
0.36
51
Authors
6
Name
Order
Citations
PageRank
Chunsheng Hua1577.40
Yasushi Makihara2101270.67
Yasushi Yagi31752186.22
Shun Iwasaki420.36
Keisuke Miyagawa520.36
Bo Li620.36