Abstract
In this paper, we explicitly consider the effect of contour fragments on the object detection performance and propose a new approach for linking edges into contour fragments. Our main observation is that the covering condition describing how contour fragments cover objects of interest is the critical factor affecting the detection accuracy. We utilize the general min-cover framework to explain an edge map. During the optimization procedure, we sequentially select best contour fragments in each connected component of the edge map for obtaining locally optimal contour fragments. Furthermore, the sequential selection of best contour fragments is reduced to an iterative parsing procedure. We conduct experiments on the ETHZ and INRIA horse datasets and compare the proposed method with other typical methods of generating contour fragments. Experimental results illustrate that our method achieves a proper covering condition and produces contour fragments that lead to better object detection performance. Besides, the proposed method is easy to compute, leading to a variety of potential real-time applications.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have