Moving vehicle detection based on dense SIFT and Extreme Learning Machine for visual surveillance

Detecting vehicles in video is a challenging problem owing to the motion of vehicles, the camera and the background and to variations of speed. This paper proposes a classifier based supervised method to detect moving vehicles from a moving camera. Dense scale invariant feature transform (dense SIFT) descriptors are used as features to describe the pattern of the object. And Extreme Learning Machine provides excellent generalization performance at fast speed. Our sample images taken by a camera in helicopter include 2000 images. Experiment results shown that this proposed method has not only good overall performance but also low computational cost.