Face recognition committee machines: dynamic vs. static structures

We propose a Dynamic Face Recognition Committee Machine (DFRCM) consisting of five well-known state-of-the-art algorithms in this paper. In previous work, we have developed a static committee machine which outperforms all the individual algorithms in the experiments. However, the weight for each expert in the committee is fixed and cannot be changed once the system is trained. We propose a dynamic architecture on the committee machine which uses the input face image in the gating network to improve the overall performances. In addition, we adopt a feedback mechanism on the committee machine to adjust the weight of an individual algorithm according to the performance of the algorithm. Detail experimental results of different algorithms and the committee machine is given to demonstrate the effectiveness of the proposed system.

• Type: Conference
• Year: 2003
• Where: ICIAP
• Authors: Ho-Man Tang, Michael R. Lyu, Irwin King
• Keywords: Committee Machine, ICIAP 2003, Image Processing, Recognition Committee Machine, Static Committee Machine