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The performance of gait recognition can be adversely affected by many sources of variation such as view angle, clothing, presence of and type of bag, posture, and occlusion, among others. In order to extract invariant gait features, we proposed a method named as GaitGAN which is based on generative adversarial networks (GAN). In the proposed method, a GAN model is taken as a regressor to generate...
Reliable identification of Human Epithelial-2 (HEp-2) cell patterns can facilitate the diagnosis of systemic autoimmune diseases. However, traditional approach requires experienced experts to manually recognize the cell patterns, which suffers from the inter-observer variability. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to simultaneously...
Gait recognition has been proved useful in human identification at a distance. But view variance of gait feature is always a great challenge because of the difference in appearance. If the view of the probe is different from that of the gallery, one view transformation model can be employed to convert the gait feature from one view to another. But most existing models need to estimate the view angle...
Reliable automatic system for Human Epithelial-2 (HEp-2) cell image classification can facilitate the diagnosis of systemic autoimmune diseases. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to address the HEp-2 specimen classification problem. The FCN in the proposed framework was adapted from VGG-16, which was trained with ICPR 2016 dataset...
As different staining patterns of HEp-2 cells indicate different diseases, the classification of Indirect Immune Fluorescence (IIF) images on Human Epithelial-2 (HEp-2) cell is important for clinical applications. Different from traditional pattern recognition techniques, we use CNN to extract more high-level features for cell images classification. Compared to the existing CNN based HEp-2 classification...
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Hyperspectral imaging has recently been introduced into face and palmprint recognition and is now drawing much attention of researchers in this area. Compared to simple 2D imaging technology, hyperspectral image can bring much more information. Due to its ablity to jointly explore the spatial-spectral domain, 3D Gabor wavelets have been successfully applied for hyperspectral palmprint recognition...
This paper presents a new feature descriptor for real-time people detection in depth images. The shape cue in depth images can reduce negative impacts of variations of clothing, lighting conditions and the complexity of backgrounds. The proposed Simplified Local Ternary Patterns (SLTP) can take advantage of depth images to describe human body shape with low computational cost. To evaluate the SLTP...
We investigate pedestrian detection in depth images. Unlike pedestrian detection in intensity images, pedestrian detection in depth images can reduce the effect of complex background and illumination variation. We propose a new feature descriptor, Histogram of Depth Difference(HDD), for this task. The proposed HDD feature descriptor can describe the depth variance in a local region as Histogram of...
The concept of active tracking is presented to simulate the characteristics of human vision in intelligent visual surveillance. The Pan/Tilt/Zoom (PTZ) camera is generally used for active tracking. In this paper, we present a novel and effective approach for active object tracking with a PTZ camera, and construct a near real-time system for indoor and outdoor scenes. The tracking algorithm of our...
Various features may be used for tracking with a mobile camera, such as color, edge, contour, texture, locomotion, key point and so on. It has been proved that combination of multiple features can increase the robustness of a tracking system. By considering the characteristics of these features, we propose the approach of employing the color and topological properties of the target in tracking. First,...
Crowd density estimation is of importance in security monitoring. Many crowd disasters happened because of the loss of control of the crowd density. This paper presents an algorithm to estimate crowd density by employing Markov Random Field (MRF). Three types of image features are extracted for estimating, and they are affected more by the neighboring features than by others, meeting the properties...
The aging of population has become a social problem and fall is a major health risk in the elderly. To this end, this paper presents a novel approach for fall detection applied to an intelligent household surveillance robot. Silhouette based features are extracted, including aspect ratio of minimal bounding box of the human silhouette, approximated elliptical eccentricity, normalized central moments...
Video surveillance in crowded areas is becoming more and more significant for public security. This paper presents a method for the detection of abnormality in crowded scenes based on the crowd motion characteristics. These characteristics includes the crowd kinetic energy and the motion directions. This approach estimates the crowd kinetic energy and the motion directions based on the optical flow...
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