ICMLA '08 Proceedings of the 2008 Seventh International Conference on Machine Learning and Applications
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Real-Time Vision-Based Vehicle Detection for Rear-End Collision Mitigation Systems
Computer Aided Systems Theory - EUROCAST 2009
Vision-based target detection in road environments
VIS'08 Proceedings of the 1st WSEAS international conference on Visualization, imaging and simulation
An obstacle detection method by fusion of radar and motion stereo
IEEE Transactions on Intelligent Transportation Systems
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The goal of this work is to propose a solution to improve a driver's safety while changing lanes on the highway. In fact, if the driver is not aware of the presence of a vehicle in his blindspot a crash can occur. In this article we propose a method to monitor the blindspot zone using video feeds and warn the driver of any dangerous situation. In order to fit in a real time embedded car safety system, we avoid using any complex techniques such as classification and learning. The blindspot monitoring algorithm we expose here is based on a features tracking approach by optical flow calculation. The features to track are chosen essentially given their motion patterns that must match those of a moving vehicle and are filtered in order to overcome the presence of noise. We can then take a decision on a car presence in the blindspot given the tracked features density. To illustrate our approach we present some results using video feeds captured on the highway.