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Obstacle detection for advanced driver assistance systems has focused on building detectors for only a few number of object categories so far, such as pedestrians and cars. However, vulnerable obstacles of other categories are often dismissed, such as wheel-chairs and baby strollers. In our work, we try to tackle this limitation by presenting an approach which is able to predict the vulnerability...
Logo identification and classification have received considerable attention from both the machine learning and computer vision communities. Vehicle logo recognition (VLR) is used to recognise accurately the manufacturer of a vehicle by using its iconic logo. A VLR system in addition to license plate recognition aims to increase the confidence of vehicle monitoring systems in private environments such...
Tracking-by-detection is an attractive paradigm for intelligent visual surveillance applications where clutter, lighting variations, target overlap and occlusions hamper conventional background modeling. However, state-of-the-art vehicle and pedestrian detectors based on discriminative classification are too computationally expensive for real-time implementation on embedded smart cameras. This paper...
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