Attentive billboards: Towards to video based customer behavior understanding

Abstract

We describe a real-time computer vision system and algorithms that extracts customer behavior information by detecting and tracking multiple people as they wait and watch advertisements on a billboard or a new product promotion at a stand. Our system segments each frame into foreground regions which contains multiple people. Foreground regions are further segmented into individuals using a temporal segmentation of foreground and motion cues and global shape constraints on 2D Silhouettes. A 2D dynamic appearance templates is used to track people. The system can provide online customer information, such as, number of people currently watching the billboard, their gender, and offline customer data, such as, how long each people looked at the billboard. Experimental results demonstrate robustness and real-time performance of the algorithm.