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Recognizing a person's motion is intuitive for humans but represents a challenging problem in machine vision. In this paper, we present a multi-disciplinary framework for recognizing human actions. We develop a novel descriptor, the Human Action Image (HAI): a physically-significant, compact representation for the motion of a person, which we derive from first principles in physics using Hamilton's...
Camera networks are being deployed for various applications like security and surveillance, disaster response and environmental modeling. However, there is little automated processing of the data. Moreover, most methods for multicamera analysis are centralized schemes that require the data to be present at a central server. In many applications, this is prohibitively expensive, both technically and...
Moving towards an dasiaalways-onpsila, dasiamobilepsila and technology driven lifestyle, people are demanding greater technical triumph to make life more exciting, convenient and trouble-free. Automation at home has already started catering to this growing need. Another major motivating factor for this is the prospect of higher energy efficiency, greater control on home from remote locations and the...
We propose genetic algorithms to improve the feature subset selection by combining the valuable outcomes from multiple feature selection methods. This paper also motivates the use of asymmetrical SVM, which focuses on two important issues. The first issue is the sample ratio bias, and the second issue is that the different types of misclassification error may have different costs, which lead to different...
We propose an improved iris recognition method to identify the person accurately by using a novel iris segmentation scheme based on the chain code and the collarette area localization. The collarette area is isolated as a personal identification pattern, which captures only the most important areas of iris complex structures, and a better recognition accuracy is achieved. The idea to use the collarette...
Biometric authentication has become increasingly popular in security systems. Recently, the systems based on the human iris, which develops a unique pattern before birth, have produced very high rates of recognition. The iris image is first blurred using a Gaussian filter, and the edge is detected using the Canny edge detection technique. An algorithm, which uses the center of the image as a starting...
In this paper, we apply the multi-objective genetic algorithm (MOGA) and asymmetrical support vector machine to improve the performance of an iris recognition system. We utilize the collarette region instead of using the complete information of iris region for recognition purpose. The deterministic feature sequence extracted from the iris images using the 2-D Gabor wavelets is applied to train the...
This paper presents an efficient iris recognition technique based on the zigzag collarette area localization and asymmetrical support vector machine. The deterministic feature sequence extracted from the iris images using the ID log-Gabor filters is applied to train the support vector machine (SVM). We use the multi- objective genetic algorithm (MOGA) to optimize the features and also to increase...
We propose an improved iris recognition method for person identification using an iris segmentation approach based on chain code and zigzag collarette area with support vector machine (SVM). The zigzag collarette area is selected as a personal identification pattern which captures only the most important areas of iris complex pattern and better recognition accuracy is achieved. The idea to use the...
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