Existing background model based change detection methods have difficulty in distinguishing between foreground and background changes when both changes are caused by the same factors. We explore the possibility of using a light field camera to resolve the problem of existing single-view camera-based approaches. We present a new change detection strategy that processes light rays captured by the light field camera. The light rays are used for three purposes: 1) generating an active surveillance field (ASF) to determine in-focus and out-focus areas, 2) evaluating focusness to determine whether the light rays come from the ASF, and 3) creating and updating light-ray background models to capture temporal changes in light rays. To investigate the effectiveness of the proposed approach, we evaluated several video sequences captured by a light field camera. Experimental results show that our change detection scheme can robustly handle challenging situations that cannot be resolved by existing single-view approaches.