Analysis of low resolution accelerometer data for continuous human activty recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2008, Pages 3337-3340

  Krishnan, Narayanan C ^a   Panchanathan, Sethuraman ^a  

^a Arizona State University   (United States)

Author keywords

Accelerometers; AdaBoost; Human activity recognition; SVM

Indexed keywords

ACCELEROMETERS; ACOUSTICS; CLASSIFIERS; GESTURE RECOGNITION; LEARNING SYSTEMS; MATERIALS HANDLING; SIGNAL PROCESSING; SPEECH; SUPPORT VECTOR MACHINES;

ADABOOST; HUMAN ACTIVITY RECOGNITION; LOW RESOLUTION; SVM;

CLASSIFICATION (OF INFORMATION);

EID: 51449085444     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2008.4518365     Document Type: Conference Paper

References (5)

1. Ling Bao and Stephen S. Intille, "Activity recognition from user-annotated acceleration data.," in Proceedings, Pervasive Computing, Second International Conference, 2004, pp. 1-17.
2. Nishkam Ravi, Nikhil Dandekar, Preetham Mysore, and Michael L. Littman, "Activity recognition from accelerometer data.," in Proceedings, The Seventeenth Innovative Applications of Artificial Intelligence Conference, 2005, pp. 1541-1546.
3. Oliver Amft, Holger Junker, and Gerhard Tröster, "Detection of eating and drinking arm gestures using inertial body-worn sensors.," in Proceedings, Ninth IEEE International Symposium on Wearable Computers (ISWC), 2005, pp. 160-163.
4. Daniel Olgun Olgun and Alex (Sandy) Pentland, "Human activity recognition: Accuracy across common locations for wearable sensors.," in Proceedings, IEEE 10th International Symposium on Wearable Computing (Student Colloquium Proceedings), 2006.
5. Jonathan Lester, Tanzeem Choudhury, Nicky Kern, Gaetano Borriello, and Blake Hannaford, "A hybrid discriminative/generative approach for modeling human activities.," in Proceedings, Nineteenth International Joint Conference on Artificial Intelligence, 2005, pp. 766-772.