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Person re-identification refers to matching people across disjoint camera views. Most existing person re-identification methods use the same feature descriptors and similarity metrics for all pedestrian pairs. However, these methods ignore that image pairs with different visual consistency conditions are sensitive to different features and metrics. In this paper, we propose to optimally organize multiple...
Smart car shows great potential in our future life and has attracted lots of interests from many research and industry communities. In this field, the technique of machine vision and recognition plays an important role, for instance, the automatic front vehicle recognition can provide driving safety information for the smart car. Lots of previous work on front vehicle recognition has been done, most...
Traffic lights recognition is important to make intelligent vehicles safe. Most of existing means to detect and recognize traffic lights focus on color, size and shape of traffic lights, which are great affected by weather and illumination conditions. In this work, we utilize deep learning and SVM classifiers to recognize traffic lights for varying illumination conditions. More specifically, a PCA...
Whole frame losses are introduced in H.264 compressed videos which are then decoded by two different decoders with different common concealment effects. The videos are seen by human observers who respond to each glitch they spot. We found that about 38% of whole frame losses of B frames are not observed by any of the subjects, and well over 58% of the B frame losses are observed by 20% or fewer of...
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