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This paper addresses two contributions for improving the accuracy and speed of preceding car detection systems. First, it proposes a feature description using Scalable Histogram of Oriented Gradient (SHOG) to solve scale problem of car region on the image. Without resizing the images to a fixed size, it is capable to extract a high-discriminated features with on the same feature space. Second, instead...
Human action recognition based on the depth maps is an important yet challenging task. In this paper, a new framework based on the 3D motion trail model (3DMTM) and Pyramid Histograms of Oriented Gradient (PHOG) is proposed to recognize human actions from sequences of depth maps. Specifically, a discriminative descriptor called 3DMTM-PHOG is proposed for depth-based human action recognition. The 3DMTM...
In the detection of human from image using statistical learning methods, the labor cost of collecting training samples and the time cost for retraining to match the target scene are major issues. One method to reduce the work involved in sample collection is transfer learning based on boosting. However, if there is a large change between the auxiliary scene and target scene, it is difficult to apply...
Action recognition is a hard problem due to the many degrees of freedom of the human body and the movement of its limbs. This is especially hard when only one camera viewpoint is available and when actions involve subtle movements. For instance, when looked from the side, checking one's watch may look very similar to crossing one's arms. In this paper, we investigate how much the recognition can be...
In this paper, we study the problem of detecting sudden pedestrian crossings to assist drivers in avoiding accidents. This application has two major requirements: to detect crossing pedestrians as early as possible just as they enter the view of the car-mounted camera and to maintain a false alarm rate as low as possible for practical purposes. Although many current sliding-window-based approaches...
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