Turn-Intent Analysis Using Body Pose for Intelligent Driver Assistance
IEEE Pervasive Computing
A general active-learning framework for on-road vehicle recognition and tracking
IEEE Transactions on Intelligent Transportation Systems
Distributed self-organizing bandwidth allocation for priority-based bus communication
Concurrency and Computation: Practice & Experience
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Awareness of what surrounds a vehicle directly affects the safe driving and maneuvering of an automobile. This paper focuses on the capture of vehicle surroundings using video inputs. Surround information or maps can help in studies of driver behavior as well as provide critical input in the development of effective driver assistance systems. A survey of literature related to surround analysis is presented, emphasizing detecting objects such as vehicles, pedestrians, and other obstacles. Omni cameras, which give a panoramic view of the surroundings, can be useful for visualizing and analyzing the nearby surroundings of the vehicle. The concept of Dynamic Panoramic Surround (DPS) map that shows the nearby surroundings of the vehicle and detects the objects of importance on the road is introduced. A novel approach for synthesizing the DPS using stereo and motion analysis of video images from a pair of omni cameras on the vehicle is developed. Successful generation of the DPS in experimental runs on an instrumented vehicle test bed is demonstrated. These experiments prove the basic feasibility and show promise of omni-camera-based DPS capture algorithm to provide useful semantic descriptors of the state of moving vehicles and obstacles in the vicinity of a vehicle