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Recent works on crowd counting have achieved promising performance by employing the Convolutional Neurol Network (CNN) based features. These works usually design a deep network to detect pedestrian heads, and then count them. In this paper, we propose a novel approach to count pedestrians effectively based on the statistical CNN features. In particular, our approach only uses the first layer features...
Existing view-invariant gait recognition methods encounter difficulties due to limited number of available gait views and varying conditions during training. This paper proposes gait partial similarity matching that assumes a 3D object shares common view surfaces in significantly different views. Detecting such surfaces aids the extraction of gait features from multiple views; 3D parametric body models...
In this paper, we present a five-part body model to recognize gestures made by Chinese traffic police in complex scenes for driver assistance systems and intelligent vehicles. Unlike most previous methods which require a training stage or a 3D measuring device to construct the body part appearance model, we propose to use the max-covering scheme to learn a five-part body model in an automatic way...
Existing methods for the registration of blurred images are efficient for the artificially blurred images or a planar registration. They are not suitable for image mosaic of the source images from a real camera with an almost fixed optical center. We propose a registration method so that a distortion-free registration on naturally captured images can be obtained. It adopts a multi-resolution and robust...
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