Sensor fusion-based people counting system using the active appearance models

The paper presents a novel robust people counting system using the active appearance model (AAM). Conventional people counting methods utilizing the monoscopic or stereoscopic image data often fail due to occasional illumination change and crowded environment. The proposed algorithm uses both the vision and depth image captured by a vision-plus-depth camera mounted on the ceiling. Then, we construct a 3D human model from the depth image using the AAM to segment and recognize human objects. Experimental results show that the proposed algorithm achieves over 97% accuracy in various testing environments.