Surface area analysis for people number estimation

An important property of surface areas of objects as observed by a calibrated monocular camera is introduced; also improved techniques to apply the property to people number estimation are proposed. Standard surface area (SSA) is defined as the surface area of the reverse projection of an image-pixel onto a plane at specific height in the real world. SSA is calculated for each pixel according to camera calibration parameters. When the target object is bound to a certain plane, for example the floor plane, the sum of SSA along with the foreground pixels of one target object becomes constant. Therefore, simple foreground detection and SSA summation yield the number of target objects. This basic idea was proposed in a prior article, but there were two major limitations. One is that the original model could not be applied to the area directly below the camera. The other is that the silhouette of the target object was limited to a simple rectangle. In this paper we propose improved techniques that remove the limitations. Slant silhouette analysis removes the first limitation, and silhouette decomposition the second. The validity and the effectiveness of the techniques are confirmed by experiments.