Comparison Between OMAP-L138 And Core i5 Processors For Real Time Object Tracking

This paper presents a real-time object tracker. The main goal of this paper was to incorporate this tracker to the real-time detection and compare the results for different processors. The frame-by-frame spatial tracking makes the algorithm computationally efficient and the appearance model matching increases the robustness. First input frames are taken, which are then subject to segmentation, thresholding and filtering. Following This paper proposes to use Image processing algorithms for the purpose of Object Identification and Tracking. In today’s world most sensing applications require some form of digital signal processing and these are implemented primarily on several processors. This paper was an attempt at developing object detection and tracking system using modern computer vision technology and to decide the better option among the processors for specific application. The paper delivers an implemented tracking system. It is stable and is applicable as a standalone system or one that could easily be embedded into an even larger system.