Abstract
The reliability of face recognition system has the characteristics of fuzziness, randomness, and continuity. In order to measure it in unconstrained scenes, we find out and quantify key broad-sense and narrow-sense influencing factors of reliability on the basis of analyzing operation states for six dynamic face recognition systems in the practical use of six public security bureaus. In this article, we propose a novel evaluation method with True Positive Identification Rate in dynamic and M:N mode and create a novel evaluation model of system reliability with the improved Fuzzy Dynamic Bayesian Network. Subsequently, we infer to solve the fuzzy reliability state probabilities of the six systems with Netica and get two most important factors with the improved fuzzy C-means algorithm. We verify the model by comparing the evaluation results with actual achievements of these systems. Finally, we find several vulnerabilities in the system with the least reliability and put forward a few optimization strategies. The proposed method combines advantages of the improved fuzzy C-means model with those of the dynamic Bayesian network to evaluate the reliability of the dynamic face recognition systems, making the evaluation results more reasonable and realistic. It starts a new research of face recognition systems in unconstrained scenes and contributes to the research on face recognition performance evaluation and system reliability analysis. Besides, the proposed method is of practical significance in improving the reliability of the systems in use.
Highlights
Nowadays, the public security situation is confronted with two major difficulties
We evaluate the reliability of dynamic face recognition systems with the improved Fuzzy Dynamic Bayesian Network model and find out important influencing factors and vulnerabilities, and put forward a few optimization strategies
We propose a novel evaluation method with True Positive Identification Rate (TPIR) in dynamic and M : N mode, create a novel reliability evaluation model of face recognition systems in unconstrained scenes, and conduct evaluation experiments on six dynamic face recognition systems in practical use
Summary
The public security situation is confronted with two major difficulties. Traditional and nontraditional security threats are intertwined. Keywords Dynamic face recognition system, reliability evaluation, Fuzzy Dynamic Bayesian Network Aimed at the problems in previous research works, we propose a relatively objective and effective reliability evaluation model with the improved Fuzzy Dynamic Bayesian Network.
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