Tracking and Size Estimation of Objects in Motion using Optical flow and K-means Clustering

Abstract

Computer vision and Robotics are promising areas in which several applications are explored during the last decade. Detection, tracking of moving objects, and classification of objects helps us in taking certain decisions in various applications. Classification of objects based on the features such as color, shape, size, speed, direction of objects in motion, etc. has numerous applications. In this paper, the Sagar G. et al. scheme [2] is extended to find the size of an object in motion which has applications in watermarking, steganography and in robotics. The proposed scheme uses K-means clustering technique to segment the objects in motion during the process of estimating the size of an object in motion.