Performance of optical flow techniques
International Journal of Computer Vision
Accuracy vs efficiency trade-offs in optical flow algorithms
Computer Vision and Image Understanding
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
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
Computer Vision and Image Understanding
Optical flow estimation using temporally oversampled video
IEEE Transactions on Image Processing
FPGA-based real-time optical-flow system
IEEE Transactions on Circuits and Systems for Video Technology
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The main goal of an overtaking monitor system is the segmentation and tracking of the overtaking vehicle. This application can be addressed through an optic flow driven scheme. We can focus on the rear mirror visual field by placing a camera on the top of it. If we drive a car, the ego-motion optic flow pattern is more or less unidirectional, i.e. all the static objects and landmarks move backwards while the overtaking cars move forward towards our vehicle. This well structured motion scenario facilitates the segmentation of regular motion patterns that correspond to the overtaking vehicle. Our approach is based on two main processing stages: first, the computation of optical flow using a novel superpipelined and fully parallelized architecture capable to extract the motion information with a frame-rate up to 148 frames per second at VGA resolution (640x480 pixels). Second, a tracking stage based on motion pattern analysis provides an estimated position of the overtaking car. We analyze the system performance, resources and show some promising results using a bank of overtaking car sequences.