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Gait is an emerging biometric technology. It enables biometric at a distance. The first step in gait recognition is the silhouette extraction. However, most of the work involves indoor controlled environment or well-exposed outdoor scenes. Furthermore, they are all applied to perspective-like pictures. This paper addresses a method for silhouette extraction on catadioptric images in indoor and uncontrolled...
Robust feature extraction within 3D environments is a crucial requirement for many autonomous robotic and tracking applications. 3D Laser range finders and cameras provide extremely rich data about an environment. However, the algorithms which attempt to compress the vast data sets produced by these sensors into features, tend to be fragile in the presence of sensor noise, or computationally expensive...
An identification method was proposed for distinguishing the bloody clams from different populations based on multi-spectral image technology. Three populations of bloody clams were collected from Korea, Shandong, and Zhejiang, respectively. The multi-spectral images of bloody clam shells were acquired by CIR MS3100 multi-spectral camera. The graylevel co-occurrence matrixes (GLCM) of the three sub-images...
In this paper, we propose a novel pattern to represent spatio-temporal information of gait appearance which is called Gait Principal Component Image (GPCI). GPCI is a grey-level image which compresses the spatiotemporal information by amplifying the dynamic variation of different body part. The detection of gait period is based on LLE coefficients and it is also a new attempt. KNN classifier is employed...
This paper presents a method for detecting people based on the co-occurrence of appearance and spatiotemporal features. Histograms of oriented gradients(HOG) are used as appearance features, and the results of pixel state analysis are used as spatiotemporal features. The pixel state analysis classifies foreground pixels as either stationary or transient. The appearance and spatiotemporal features...
In this paper, we propose a fast and stable pedestrian recognition approach using the features from both stereo vision and HOG (Histogram of Oriented Gradient) filter. It inquires the histogram of disparity from the stereo images and builds a mask image to extract the features from foreground regions exclusively. HOG and PCA (Principal Component Analysis) are then applied to the foreground edge image...
Multi-focus image fusion aims at overcoming imaging cameras' finite depth of field by combining information from multiple images with the same scene. In this paper, a regional firing intensity (RFI) is defined, which is based on the statistical characteristic in local window of neuron firing times when pulse coupled neural networks (PCNN) is utilized in the image fusion. A novel image fusion algorithm...
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