DocumentCode
1892258
Title
Trajectory analysis and prediction for improved pedestrian safety: Integrated framework and evaluations
Author
Mogelmose, Andreas ; Trivedi, Mohan M. ; Moeslund, Thomas B.
Author_Institution
Visual Anal. of People Lab., Aalborg Univ., Aalborg, Denmark
fYear
2015
fDate
June 28 2015-July 1 2015
Firstpage
330
Lastpage
335
Abstract
This paper presents a monocular and purely vision based pedestrian trajectory tracking and prediction framework with integrated map-based hazard inference. In Advanced Driver Assistance systems research, a lot of effort has been put into pedestrian detection over the last decade, and several pedestrian detection systems are indeed showing impressive results. Considerably less effort has been put into processing the detections further. We present a tracking system for pedestrians, which based on detection bounding boxes tracks pedestrians and is able to predict their positions in the near future. The tracking system is combined with a module which, based on the car´s GPS position acquires a map and uses the road information in the map to know where the car can drive. Then the system warns the driver about pedestrians at risk, by combining the information about hazardous areas for pedestrians with a probabilistic position prediction for all observed pedestrians.
Keywords
computer vision; inference mechanisms; intelligent transportation systems; pedestrians; probability; road safety; ADAS; advanced driver assistance systems; map-based hazard inference; pedestrian safety; probabilistic position prediction; trajectory analysis; trajectory prediction; vision based pedestrian trajectory tracking; Atmospheric measurements; Cameras; Hazards; Particle measurements; Roads; Tracking; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium (IV), 2015 IEEE
Conference_Location
Seoul
Type
conf
DOI
10.1109/IVS.2015.7225707
Filename
7225707
Link To Document