Poster Abstract: CAR - A deep learning structure for concurrent activity recognition
Proceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017
Activity recognition; Deep learning; Multimodel; Passive RFID
© 2017 ACM. We introduce the Concurrent Activity Recognizer (CAR) - an efficient deep learning structure that recognizes complex concurrent teamwork activities from multimodal data. We implemented the system in a challenging medical setting, where it recognizes 35 different activities using Kinect depth video and data from passive RFID tags on 25 types of medical objects. Our preliminary results showed our system achieved an 84% average accuracy with 0.20 F1-Score.
Zhang, Y., Li, X., Zhang, J., Chen, S., Zhou, M., Farneth, R., Marsic, I., & Burd, R. (2017). Poster Abstract: CAR - A deep learning structure for concurrent activity recognition. Proceedings - 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2017, (). http://dx.doi.org/10.1145/3055031.3055058