TY - GEN
T1 - Personal driving diary
T2 - 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011
AU - Ryoo, M. S.
AU - Lee, Jae Yeong
AU - Joung, Ji Hoon
AU - Choi, Sunglok
AU - Yu, Wonpil
PY - 2011
Y1 - 2011
N2 - In this paper, we introduce the concept of personal driving diary. A personal driving diary is a multimedia archive of a person's daily driving experience, describing important driving events of the user with annotated videos. This paper presents an automated system that constructs such multimedia diary by analyzing videos obtained from a vehicle-mounted camera. The proposed system recognizes important interactions between the driving vehicle and the others from videos (e.g. accident, overtaking,⋯), and labels them together with its contextual knowledge on the vehicle (e.g. its physical location on the map) to construct an event log. A novel decision tree based activity recognizer that incrementally learns driving events from first-person view videos is designed. The constructed diary enables efficient searching and event-based browsing of video clips, which helps the user to retrieve videos of dangerous situations and analyze his/her driving habits statistically. Our experiment confirms that the proposed system reliably generates driving diaries by annotating learned vehicle events.
AB - In this paper, we introduce the concept of personal driving diary. A personal driving diary is a multimedia archive of a person's daily driving experience, describing important driving events of the user with annotated videos. This paper presents an automated system that constructs such multimedia diary by analyzing videos obtained from a vehicle-mounted camera. The proposed system recognizes important interactions between the driving vehicle and the others from videos (e.g. accident, overtaking,⋯), and labels them together with its contextual knowledge on the vehicle (e.g. its physical location on the map) to construct an event log. A novel decision tree based activity recognizer that incrementally learns driving events from first-person view videos is designed. The constructed diary enables efficient searching and event-based browsing of video clips, which helps the user to retrieve videos of dangerous situations and analyze his/her driving habits statistically. Our experiment confirms that the proposed system reliably generates driving diaries by annotating learned vehicle events.
UR - http://www.scopus.com/inward/record.url?scp=79952504651&partnerID=8YFLogxK
U2 - 10.1109/WACV.2011.5711563
DO - 10.1109/WACV.2011.5711563
M3 - Conference contribution
AN - SCOPUS:79952504651
SN - 9781424494965
T3 - 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011
SP - 628
EP - 633
BT - 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011
Y2 - 5 January 2011 through 7 January 2011
ER -