Gesture recognition plays an important role in human computer Interaction for intelligent computing. Major applications like Gaming, Robotics and Automated Homes uses gesture recognition techniques which diminishes the usage of mechanical devices. The main goal of my thesis is to interpret SWAT team gestures using different types of sensors. Accelerometer and flex sensors were explored extensively to build a prototype for soldiers to communicate in the absence of line of sight. Arm movements were recognized by flex sensors and motion gestures by Accelerometers. Accelerometers are used to measure acceleration in respect to movement of the sensor in 3D. Flex sensors changes its resistance based on the amount of bend in the sensor. SVM is the classification algorithm used for classification of the samples. LIBSVM (Library for Support Vector Machines) is integrated software for support vector classification, regression and distribution estimation which supports multi class classification. Sensors data is connected to the WI micro dig to digitize the signal and to transmit it wirelessly to the computing device. Feature extraction and Signal windowing were the two major factors which contribute for the accuracy of the system. Mean Average value and Standard Deviation are the two features considered for accelerometer sensor data …

Manual video analysis is apparently a tedious task. An efficient solution is of highly importance to automate the process and to assist operators. A major goal of video analysis is understanding and recognizing human activities captured by surveillance cameras, a very challenging problem; the activities can be either individual or interactional among multiple objects. It involves extraction of relevant spatial and temporal information from visual images. Most video analytics systems are constrained by specific environmental situations. Different domains may require different specific knowledge to express characteristics of interesting events. Spatial-temporal trajectories have been utilized to capture motion characteristics of activities. The focus of this dissertation is on how trajectories are utilized in assist in developing video analytic system in the context of surveillance. The research as reported in this dissertation begins real-time highway traffic monitoring and dynamic traffic pattern analysis and in the end generalize the knowledge to event and activity analysis in a broader context. The main contributions are: the use of the graph-theoretic dominant set approach to the classification of traffic trajectories; the ability to first partition the trajectory clusters using entry and exit point awareness to significantly improve the clustering effectiveness and to reduce the computational time …