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The ability to classify a vehicle is of extreme importance for both civilian and non-civilian applications. For non-civilian applications the state-of-the-art leaves much to be desired, as hierarchal and real-time classification have yet to be truly investigated. This paper provides a survey of the current state-of-the-art in vehicle classification and provides recommendations for future research...
Vision-based object detection from a moving platform becomes particularly challenging in the field of advanced driver assistance systems (ADAS). In this context, onboard vision-based vehicle verification strategies become critical, facing challenges derived from the variability of vehicles appearance, illumination, and vehicle speed. In this paper, an optimized HOG configuration for onboard vehicle...
In this paper the authors propose a pedestrian detection system based on discrete features in infrared images. Unique keypoints are searched for in the images around which a descriptor, based on the histogram of the phase congruency orientation, is extracted. These descriptors are matched with defined regions of the body of a pedestrian. In case of a match, it creates a region of interest in the image,...
In this paper, we propose an object detection method that uses Joint features combined from multiple Histograms of Oriented Gradients (HOG) feature using two-stage boosting. There has been much research in recent years on statistical training methods and object detection methods that combine low-level features obtained from local areas. In our approach, multiple low-level HOG features are combined...
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