DocumentCode :
732345
Title :
Motion classification of pedestrian walking behaviors on the sidewalk
Author :
Gihyun Han ; Heejae Choi ; Bongsob Song
Author_Institution :
Dept. of Mech. Eng., Ajou Univ., Suwon, South Korea
fYear :
2015
fDate :
7-10 July 2015
Firstpage :
228
Lastpage :
231
Abstract :
This paper proposes a motion classification algorithm of pedestrian walking behavior by fusing radar and vision sensors. Under the situation that the pedestrian is detected by both two heterogeneous sensors, it will be discussed how quickly the intention of pedestrian on the sidewalk, e.g., stop, crossing, and walking along the road, is determined. While most of previous researches use lateral position of pedestrian as a feature for classification, the velocity with respect to lane at the sidewalk is estimated and used as an additional feature. Support vector machine as a classifier is used for motion classification of walking behaviors. Finally, the proposed algorithm will be validated via driving test data.
Keywords :
gait analysis; image motion analysis; image sensors; pedestrians; radar imaging; road traffic; sensor fusion; support vector machines; traffic engineering computing; driving test data; heterogeneous sensors; motion classification algorithm; pedestrian walking behaviors; radar; sidewalk; support vector machine; vision sensors; Classification algorithms; Estimation; Legged locomotion; Radar; Sensors; Support vector machines; Vehicles; Automatic emergency braking; Convex optimization; Motion classification; Support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Ubiquitous and Future Networks (ICUFN), 2015 Seventh International Conference on
Conference_Location :
Sapporo
ISSN :
2288-0712
Type :
conf
DOI :
10.1109/ICUFN.2015.7182539
Filename :
7182539
Link To Document :
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