Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Toward vision-based intelligent navigator: its concept and prototype
IEEE Transactions on Intelligent Transportation Systems
Computer vision algorithms for intersection monitoring
IEEE Transactions on Intelligent Transportation Systems
VIRTUOUS: vision-based road transportation for unmanned operation on urban-like scenarios
IEEE Transactions on Intelligent Transportation Systems
Sub-block interchange for lossless image compression
IEEE Transactions on Consumer Electronics
Crossing road monitoring system based on adaptive decision for illegal situation
Applied Soft Computing
Image-Based absolute positioning system for mobile robot navigation
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
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A 'Moving Window' scheme for detecting lanes, obstacles and corridor environments from the images captured by a CCD camera in an automobile or mobile robot is proposed. Processing the input dynamic images in real time requires high performance hardware as well as efficient software. In order to relieve these requirements for detecting the useful information from the images in real time, a 'Moving Window' scheme is proposed. For each image frame, the 'Moving Window' is newly defined and it is moved in a certain direction that is predicted by the Kalman filtering technique. By detecting the useful information, it becomes possible to search the obstacles within the driving lane of an automobile or mobile robot. The obstacle can be verified through the correlation between the stochastic characteristics of the suspected obstacle and the actual obstacle in a database. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of the freeway and the corridor driving.