A Review and Comparison of Measures for Automatic Video Surveillance Systems. (8th July 2008)

• Record Type: Journal Article
• Authors: Baumann, Axel; Boltz, Marco; Ebling, Julia; Koenig, Matthias; Loos, Hartmut S.; Merkel, Marcel; Niem, Wolfgang; Warzelhan, Jan Karl; Yu, Jie
• Other Names: Cavallaro Andrea Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2008(2008)
• Publication Date: 2008-07-08
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2008/824726
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : Today's video surveillance systems are increasingly equipped with video content analysis for a great variety of applications. However, reliability and robustness of video content analysis algorithms remain an issue. They have to be measured against ground truth data in order to quantify the performance and advancements of new algorithms. Therefore, a variety of measures have been proposed in the literature, but there has neither been a systematic overview nor an evaluation of measures for specific video analysis tasks yet. This paper provides a systematic review of measures and compares their effectiveness for specific aspects, such as segmentation, tracking, and event detection. Focus is drawn on details like normalization issues, robustness, and representativeness. A software framework is introduced for continuously evaluating and documenting the performance of video surveillance systems. Based on many years of experience, a new set of representative measures is proposed as a fundamental part of an evaluation framework.