Object detection and tracking is one of the key tasks performed in video surveillance. The objects present in the area under surveillance is studied and analyzed with reference to the context. This plays a pivotal role in detecting and predicting anomalies based on the behavioral traits of objects observed under the surveillance region. Optical flow is one of the computer vision based approaches that is used for tracking the precise movement of objects. Several optical flow algorithms have been used to track and study the movement of objects. This work is motivated towards carrying out a thorough study different optical flow techniques and comparing the features of different optical flow approaches and implementing them for real time detection and tracking of objects in real time environment.

In this present work, the impact of blending n-butyl alcohol, a next generation biofuel with jatropha biodiesel on the performance of a diesel engine are examined. Tests were performed on a constant speed compression ignition engine using n-butyl alcohol / jatropha biodiesel blends. N-butyl alcohol was added to jatropha biodiesel by 10, 20 and 30% by volume. Performance parameters namely break thermal efficiency (BTE), Brake specific fuel consumption (BSFC) and Exhaust gas temperature (EGT) were analyzed in this work. It was experimentally found that by adding n-butyl alcohol to neat jatropha biodiesel, significant reduction in viscosity was observed. In addition, break thermal efficiency was increased by 0.8 % due to improved atomization of the blends. Further, brake specific fuel and exhaust gas temperature was further reduced due to lower viscosity and improved combustion rate with addition of n-butyl alcohol to jatropha biodiesel.