Evaluation Of Target Detection Algorithms Based On Background Modeling

Background modeling is the most important and most widely used method of movingtarget detection. Many researchers have carried out extensive and in-depth study in thetheory and practical application of this method, and get a lot of achievements. Most ofthese algorithms are developed to solve the special problem in the specific scene, so theycannot adapt to the change of scene. A few algorithms take into account the general scene,but it’s difficult to define their scope. For the lack of precise quantitative targets, they canonly do qualitative description. At present, few scholars could evaluate performance of thebackground modeling algorithms, clarify the right occasions of the algorithms and theiradvantages and disadvantages. It’s more and more urgently necessary to effectivelyevaluate a large number of target detection algorithms which have been proposed or arebeing proposed, and evaluate their performance to improve the algorithms and proposenew algorithms. Performance evaluation of target detection algorithms is very critical tothe research and development of target detection and recognition algorithms and systems,and also critical to the boundary definition and adaptability of the algorithms and systems,and so to the improvement of the system performance.In this paper, we evaluate five representative background modeling algorithm appliedto image sequences and study the performance evaluation theories, methods andenvironmental support of the general target detection algorithm, in order to provide atheoretical basis and testing platform for development of algorithm and system. We studyfrom three aspects: first, the framework of background modeling algorit hm andperformance evaluation; second, the general framework of background modelingalgorithm applied to image sequences; finally, analysing the existing algorithms throughthe test results to support the development of new algorithms.In this paper, through analysing status quo of the performance evaluation of thebackground modeling algorithm, we present the view on putting the study and performance evaluation of algorithm into a unified framework. The basic principles andmethods of performance evaluation are discussed, and we also explore the organizationalstructure and software support platform of the performance evaluation of the algorithm.