Title :
Fusing RFID and computer vision for probabilistic tag localization
Author :
Goller, Michael ; Feichtenhofer, Christoph ; Pinz, Axel
Author_Institution :
Enso Detego GmbH, Graz, Austria
Abstract :
The combination of RFID and computer vision systems is an effective approach to mitigate the limited tag localization capabilities of current RFID deployments. In this paper, we present a hybrid RFID and computer vision system for localization and tracking of RFID tags. The proposed system combines the information from the two complementary sensor modalities in a probabilistic manner and provides a high degree of flexibility. In addition, we introduce a robust data association method which is crucial for the application in practical scenarios. To demonstrate the performance of the proposed system, we conduct a series of experiments in an article surveillance setup. This is a frequent application for RFID systems in retail where previous approaches solely based on RFID localization have difficulties due to false alarms triggered by stationary tags. Our evaluation shows that the fusion of RFID and computer vision provides robustness to false positive observations and allows for a reliable system operation.
Keywords :
computer vision; object tracking; radiofrequency identification; retail data processing; sensor fusion; sensor placement; surveillance; RFID deployment; RFID fusion; RFID tag localization; RFID tag tracking; complementary sensor modality; computer vision; electronic article surveillance; false alarm triggering; hybrid RFID system; probabilistic tag localization; retail; robust data association method; stationary tags; Antenna measurements; Antenna radiation patterns; Cameras; Radiofrequency identification; Robustness; Trajectory;
Conference_Titel :
RFID (IEEE RFID), 2014 IEEE International Conference on
Conference_Location :
Orlando, FL
DOI :
10.1109/RFID.2014.6810717