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This paper presents a vision-based vehicle detection system in the infrared (IR) and vision system using an effective feature extraction and algorithm. This system follows two steps: Hypothesis Generation (HG) method and Hypothesis Verification (HV) method. In HG method, vertical and horizontal edges are used. To extract these edges effectively a neighborhood gradient prediction(NGP) edge detection...
Gait has received much interest from the biometric society in the vision field due to its utility in walker identification. In this paper, we present a regularized eigenspace-based gait recognition system for human identification. First, motion contour image (MCI) is extracted from walking sequences. In training phase, eigenfeature regularization and extraction (ERE) is applied to the gallery motion...
Gait recognition has recently attracted increasing interest from the biometric society. In this paper, we present a gait recognition system based on the fusion of multiple gait cycles using a new gait representation. First, a gait sequence is automatically partitioned into multiple gait cycles by finding the local minima of width signal. After gait cycle partitioning, we extract a new gait feature...
Gait recognition systems have recently attracted much interest from biometric researchers. In this work, we present an alternative gait representation of width vector profile. The proposed model-free gait representation, width vector mean, is defined by the arithmetic mean of width vector profiles obtained from a gait sequence. Different gait feature are extracted from the width vector mean such the...
In this paper, a gait recognition system fusing multiple gait cycles is presented for human identification. First, the cycle length is estimated by calculating the autocorrelation of the foreground sum signal. After gait cycle partitioning, we extract two kinds of gait feature, gait energy image (GEI) and motion silhouette image (MSI). To identify individual, the outputs of the nearest neighbor classifiers...
This paper presents a multi-view gait recognition algorithm for identification at a distance. We make use of two well known and effective gait representations namely Motion Silhouette Image (MSI) and gait energy image (GEI). MSI and GEI inherently capture the spatiotemporal characteristics of gait. We show that the individual recognition performance of MSI and GEI can be improved by using a fusion...
In this paper, we have proposed a new representation for human gait recognition which is called as mass vector. The mass vector along a given row is defined as the number of pixels with a nonzero value in a given row of the binarized silhouette of a walking person. Sequences of temporally ordered mass vector are used to represent a gait of an individual. Besides, different gait features are extracted...
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