Abstract

The selection of optimal camera configurations (camera locations, ori- entations etc.) for multi-camera networks remains an unsolved problem. Previ- ous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale net- works. To tackle this, we introduce a statistical formulation of the optimal selection of camera configurations as well as propose a Trans-Dimensional Simulated An- nealing (TDSA) algorithm to effectively solve the problem. We compare our ap- proach with a state-of-the-art method based on Binary Integer Programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than 2 alterna- tive heuristics designed to deal with the scalability issue of BIP.