EARLY DETECTION OF SECURITY CAMERA TAMPERING FOR VIDEO CONTENT ANALYSIS SYSTEM

Abstract

The objective of this paper is to early detect security camera tampering with the proposed algorithm to address the two major issues of camera tampering attacks such as camera defocus and camera-lens block. These anomaly events such as screen shaking, flickering, color casting and lens cover significantly impact the effectiveness of video surveillance systems. The purpose of the algorithm is to measure the distance between a moving object and the camera's field of view.  Because of this close distance estimation can detect camera tampering earlier. To evaluate the performance of the proposed algorithm, three video datasets with various types of camera attacks were tested with 64 anomalous events in video sequences. The proposed algorithm demonstrated its efficiency with an average of 3.1% missing events and an average of 7.8% false alarms in the experimental results.