High Performance Object Detection on Big Video Data Using GPUs High resolution cameras have become inexpensive, compact and ubiquitously present in smart phones and surveillance systems. As a result huge volumes of images and video data are being generated daily. This availability of big video data has created challenges to video processing and analysis. Novel and scalable data management and processing frameworks are needed to meet the challenges posed by the big video data. This paper focuses on the first step in meeting this challenge that is to have high performance processing of big video data using GPUs. Parallel implementation of video object detection algorithm is presented along with fine grain optimization techniques and algorithm innovation. Experimental results show significant speedups of the algorithms resulting in real time processing of HD and beyond HD (like panoramic) resolution videos.