Toward recognition of short and non-repetitive activities from wearable sensors

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4794 LNCS, Issue , 2007, Pages 142-158

  Zinnen, Andreas ^a   Van Laerhoven, Kristof ^a   Schiele, Bernt ^a  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Activity recognition; HMMs; Postures

Indexed keywords

COMPUTATION THEORY; ELECTRONIC DOCUMENT IDENTIFICATION SYSTEMS; PATTERN RECOGNITION; SENSOR NETWORKS;

HIGH DISCRIMINATIVE POWER; WEARABLE SENSORS;

WEARABLE COMPUTERS;

EID: 38149092649     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-76652-0_9     Document Type: Conference Paper

References (16)

1. Huynh, T., Schiele, B.: Analyzing features for activity recognition. In: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services, ACM Press, New York, USA (2005)
2. Lukowicz, P., Ward, J., Junker, H., Staeger, M., Troester, G., Atrash, A., Starner, S.: Recognizing workshop activity using body worn microphones and accelerometers. In: Pervasive Computing (2005)
3. Bao, L., Intille, S.: Activity recognition from user-annotated acceleration data. In: Mattern, F. (ed.) Pervasive Computing (2004)
4. Minnen, D., Starner, T., Essa, I., Isbell, C.: Discovering Characteristic Actions from On-Body Sensor Data. In: Proceedings of the Tenth IEEE International Symposium on Wearable Computers (ISWC), IEEE Computer Society Press, Los Alamitos (2006)
5. Clarkson, B., Pentland, A.: Unsupervised clustering of ambulatory audio and video. In: Icassp (1999)
6. Oliver, N., Horvitz, E., Garg, A.: Layered representations for human activity recognition. In: Proceedings of the Fourth IEEE Int. Conf. on Multimodal Interfaces, IEEE Computer Society Press, Los Alamitos (2002)
7. Kela, J., Korpipää, P., Mäntyjärvi, J., Kallio, S., Savino, G., Jozzo, L., Marca, D.: Accelerometer-based gesture control for a design environment. Personal Ubiquitous Comput. (2006)
8. Mäntylaä, Mäntyjärvi, Seppänen, Tuulari: Hand gesture recognition of a mobile device user. In: The Proceedings of the international IEEE conference on multimedia and expo (2000)
9. Hoffman, F., Heyer, P., Hommel, G.: Velocity profile based recognition of dynamic gestures with discrete hidden markov models. In: Proceedings of gesture workshop (1997)
10. Iacucci, G., Kela, J., Pehkonen, P.: Computational support to record and reexperience visits. Personal and ubiquitous computing 8(2) (2004)
11. Ward, J., Lukowicz, P., Tröster, G.: Gesture spotting using wrist worn microphone and 3-axis accelerometer. In: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)
12. Lukowicz, P., Ward, J., Junker, H., Stager, M., Tröster, G., Atrash, A., Starner, T.: Recognizing Workshop Activity Using Body Worn Microphones and Accelerometers. LNCS (2004)
13. Murphy, K.: Hidden Markov Model (HMM) Toolbox for Matlab, http://www.cs.ubc.ca/murphyk/Software/HMM/hmm.html
14. Stiefmeier, T., Ogris, G., Junker, H., Lukowicz, P., Tröster, G.: Combining Motion Sensors and Ultrasonic Hands Tracking for Continuous Activity Recognition in a Maintenance Scenario. In: 10th IEEE International Symposium on Wearable Computers (2006)
15. Clarkson, B., Sawhney, N., Pentland, A.: Auditory context awareness in wearable computing. In: Workshop on Perceptual User Interfaces (1998) 16. http://xsens.com/
16. Rabiner, L.: A Tutorial On Hidden Markov Models. Proceedings of the IEEE (1989)