Dynamic Hybrid Algorithms for MAP Inference in Discrete MRFs

—In this paper, we present novel techniques that improve the computational and memory efficiency of algorithms for solving multi-label energy functions arising from discrete MRFs or CRFs. These methods are motivated by the observations that the performance of minimization algorithms depends on: (a) the initialization used for the primal and dual variables; and (b) the number of primal variables involved in the energy function. Our first method (dynamic α-expansion) works by ‘recycling’ results from previous problem instances. The second method simplifies the energy function by ‘reducing’ the number of unknown variables present in the problem. Further, we show that it can also be used to generate a good initialization for the dynamic α-expansion algorithm by ‘reusing’ dual variables. We test the performance of our methods on energy functions encountered in the problems of stereo matching, and colour and object based segmentation. Experimental results show that our met...

• Type: Journal
• Year: 2010
• Where: PAMI
• Authors: Karteek Alahari, Pushmeet Kohli, Philip H. S. Torr
• Keywords: Algorithm, Dual Variables, Energy Functions, PAMI 2010