Zengshuai Qiu

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Video object tracking is an important method of traffic data collection in ITS. This paper implements an approach for detecting traffic objects in urban traffic scenes by means of feature-based reasoning on visual data, and tries to track and classify traffic objects with self-defined features. An adaptive Kalman prediction algorithm is presented to improve(More)
Multiple images have been widely used for scene understanding and navigation of unmanned ground vehicles in long term operations. However, as the amount of visual data in multiple images is huge, the cumulative error in many cases becomes untenable. This paper proposes a novel method that can extract features from a large dataset of multiple images(More)
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