Midground object detection in real world video scenes

Traditional video scene analysis depends on accurate background modeling to identify salient foreground objects. However, in many important surveillance applications, saliency is defined by the appearance of a new non-ephemeral object that is between the foreground and background. This midground realm is defined by a temporal window following the object’s appearance; but it also depends on adaptive background modeling to allow detection with scene variations (e.g., occlusion, small illumination changes). The human visual system is illsuited for midground detection. For example, when surveying a busy airline terminal, it is difficult (but important) to detect an unattended bag which appears in the scene. This paper introduces a midground detection technique which emphasizes computational and storage efficiency. The approach uses a new adaptive, pixel-level modeling technique derived from existing backgrounding methods. Experimental results demonstrate that this technique can accurate...

• Type: Conference
• Year: 2007
• Where: AVSS
• Authors: Brian Valentine, Senyo Apewokin, Linda M. Wills, D. Scott Wills, Antonio Gentile
• Keywords: AVSS 2007, Background Modeling, Midground Detection, Salient Foreground Objects, Signal Processing