Object Movement Management System via Integration of Stable Image Changes in Multiple Viewpoints

This paper proposes an object movement detection system covering large areas of a room by using multiple cam-eras. When object movement detection for whole of a room is performed, there are several challenging difficulties: sizes of objects on the camera images are small, non-objects such as humans also exist on the images, objects are sometimes difficult to detect in the specific viewpoints because of occlusion by humans or furniture or color similarity to near objects. In this work, we propose an object movement detection method by integrating multiple viewpoints via features extracted from “stable changes” on each viewpoint. To discriminate whether object or non-object, we focus on motion of changed regions. Experiment in a room environment shows the multiple view integration method with the color and position features improves recall rate of object detection performance.