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Personal Driving Diary: Automated Recognition of Driving Events from First-Person Videos
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- Authors
- M.S. Ryoo, Sunglok Choi, Ji Hoon Joung, Jae-Yeong Lee, Wonpil Yu
- Issue Date
- 2013-10
- Citation
- Computer Vision and Image Understanding, v.117, no.10, pp.1299-1312
- ISSN
- 1077-3142
- Publisher
- Elsevier
- Language
- English
- Type
- Journal Article
- Abstract
- 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 other actors in videos (e.g., accident, overtaking, etc.), and labels them together with its contextual knowledge on the vehicle (e.g., mean velocity) to construct an event log. A decision tree based activity recognizer is designed, detecting driving events of vehicles and pedestrians from the first-person view videos by analyzing their trajectories and spatio-temporal relationships. The constructed diary enables efficient searching and event-based browsing of video clips, which helps the users when retrieving videos of dangerous situations. Our experiment confirms that the proposed system reliably generates driving diaries by annotating the vehicle events learned from training examples. © 2013 Elsevier Inc. All rights reserved.
- KSP Keywords
- Decision Tree(DT), Driving experience, Event Logs, Event-Based, Mean velocity, Training examples, Tree-based, Vehicle-mounted, Video clips, an automated system, driving events