Real-Time Salient Closed Boundary Tracking using Perceptual Grouping and Shape Priors

Xuebin Qin, Shida He, Zichen Zhang, Masood Dehghan, Martin Jagersand
2017 Procedings of the British Machine Vision Conference 2017   unpublished
In this paper, we propose a real-time method for accurate salient closed boundary tracking via a combination of shape constraints and perceptual grouping on edge fragments. Particularly, we encode the Gestalt law of proximity and the prior shape constraint in a novel ratio-form grouping cost. The proximity and prior constraint are depicted by the relative gap length and average distance difference along the to-be-tracked boundary with respect to its area. We build a graph using the detected
more » ... fragments and in-between gaps. The grouping problem is formulated as searching for a special cycle in this graph with a minimum grouping cost. To reduce the search space and achieve real-time performance, we propose a set of novel techniques for efficient edge fragments splitting and filtering. We evaluate this method on a public real-world video dataset against other methods. The average alignment errors of different sequences achieved by our method are mostly less than 1 pixel, an improvement over state-of-the-art methods.
doi:10.5244/c.31.12 fatcat:tw4ccnfsbrbyfgnay2fyk3wvgy