Object Detection and Tracking using Multiple Features Extraction

In most of the video analysis applications, object detection and tracking play vital role. Most algorithms fail to predict multiple objects with varying orientation. this paper, goal is identify track using different feature extraction methods like Locality Sensitive Histogram, Histogram Oriented Gradients Edges. These features are subjected train classifier that can detect orientations. Experimental results performance evaluation depicts proposed method which uses LSH performs well an increased accuracy 98%. This precisely be utilized under scale pose variations.