A Novel Search Technique of Motion Estimation for Video Compression

Video Compression is highly demanded now a days as due to the fact that in the field of entertainment, medicine and communication there is high demand for digital video technology. For the effective removal of temporal redundancy between the frames for better video compression Motion estimation techniques plays a major role. Block based motion estimation has been widely used for video coding. One such method is the Hierarchical Search Technique for BMA. By amalgamating the three different search algorithms like New three step search, New Full search and New Cross diamond search a novel hierarchical search methodology is proposed. Sub- sampling the original image into additional two levels is done and thereby the New Diamond search algorithm and a new three-step search algorithm are used in the bottom two levels and the Full Search is performed on the highest level where the complexity is relatively low. In terms of PSNR with reduced complexity this new proposed algorithm showed better performance

Overview of Environment Perception for Intelligent Vehicles

This paper presents a comprehensive literature review on environment perception for intelligent vehicles. The state-of-the-art algorithms and modeling methods for intelligent vehicles are given, with a summary of their pros and cons. A special attention is paid to methods for lane and road detection, traffic sign recognition, vehicle tracking, behavior analysis, and scene understanding. In addition, we provide information about datasets, common performance analysis, and perspectives on future research directions in this area

Vision-based control of multi-agent systems

Scope and Methodology of Study: Creating systems with multiple autonomous vehicles places severe demands on the design of decision-making supervisors, cooperative control schemes, and communication strategies. In last years, several approaches have been developed in the literature. Most of them solve the vehicle coordination problem assuming some kind of communications between team members. However, communications make the group sensitive to failure and restrict the applicability of the controllers to teams of friendly robots. This dissertation deals with the problem of designing decentralized controllers that use just local sensor information to achieve some group goals.Findings and Conclusions: This dissertation presents a decentralized architecture for vision-based stabilization of unmanned vehicles moving in formation. The architecture consists of two main components: (i) a vision system, and (ii) vision-based control algorithms. The vision system is capable of recognizing and localizing robots. It is a model-based scheme composed of three main components: image acquisition and processing, robot identification, and pose estimation.Using vision information, we address the problem of stabilizing groups of mobile robots in leader- or two leader-follower formations. The strategies use relative pose between a robot and its designated leader or leaders to achieve formation objectives. Several leader-follower formation control algorithms, which ensure asymptotic coordinated motion, are described and compared. Lyapunov's stability theory-based analysis and numerical simulations in a realistic tridimensional environment show the stability properties of the control approaches