The main and important objective of tracking an object is to segment a ROI from a given video scene. Once the object is tracked it is continued to track its motion occlusion and most importantly its position. Detection and classifications of objects are the previous steps to track an object in a given video. Object detection process is done to check the existence or presence of objects in a given video and also to exactly locate the existed object. After detection, the objects that are detected are classified into varieties of categories namely humans, pedestrian, vehicles and also other objects which are under motion. Object tracking process is done by monitoring the objects temporal as well as spatial changes throughout a given video sequence which includes the presence, size and position etc. Object tracking has been used in numerous applications like video surveillance, artificial intelligence, traffic monitoring and also in video animations. This work presents a short-term survey of various object detection algorithms which is available in literature survey together with analysis and also a comparative learning of diverse detection techniques used.