HMM machine learning and inference for Activities of Daily Living recognition

Journal of Supercomputing

Volumn 54, Issue 1, 2010, Pages 29-42

  Cheng, Bo Chao ^a   Tsai, Yi An ^a   Liao, Guo Tan ^a   Byeon, Eui Seok ^b  

^a NATIONAL CHUNG CHENG UNIVERSITY   (Taiwan)

^b SunMoon University   (South Korea)

Author keywords

Activity Recognition; ADL; Baum welch algorithm; Context Aware Computing System; Hidden Markov Model; Viterbi algorithm

Indexed keywords

ACTIVITY RECOGNITION; ADL; BAUM-WELCH ALGORITHMS; CONTEXT-AWARE COMPUTING; VITERBI;

ARTS COMPUTING; HIDDEN MARKOV MODELS; MATHEMATICAL MODELS; VITERBI ALGORITHM;

INFERENCE ENGINES;

EID: 78149415969     PISSN: 09208542     EISSN: 15730484     Source Type: Journal    
DOI: 10.1007/s11227-009-0335-0     Document Type: Article

References (13)

1. Ayala M, Adjouadi M (2003) An optimized artificial neural network approach for epileptiform activity recognition. In: Proceedings of the IASTED international conference on modeling and simulation, ISBN: 0-88986-337-7, Palm Springs, CA, USA, February, pp 342-347
2. Baum EL, Petrie T, Soules G, Weiss N (1970) A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Ann Math Stat 41(1):164-171. doi:10.1214/aoms/1177697196
3. Bodor R, Jackson B, Papanikolopoulos N (2003) Vision-based human tracking and activity recognition. In: Proceedings of the 11th Mediterranean conf on control and automation, Jun. 2003
4. Freitag D, McCallum A (1999) Information extraction with HMMs and shrinkage. In: Proceedings of the AAAI-99 workshop on machine learning for information extraction
5. Freitag D, McCallum A (2000) Information extraction with HMM structures learned by stochastic optimization. In: AAAI/IAAI 2000, pp 584-589
6. Oliver N, Horvitz E, Garg A (2002) Layered representations for human activity recognition. In: Multimodal interfaces, proceedings, fourth IEEE int'l conf on 14-16 Oct, pp 3-8
7. Oliver N, Horvitz e (2005) A comparison of HMMs and dynamic Bayesian networks for recognizing office activities. User modeling, pp 199-209
8. Patterson D et al (2005) Fine-grained activity recognition by aggregating abstract object usage. In: Ninth IEEE international symposium on wearable computers (ISWC 2005), Osaka, Japan, 18-21 October, pp 44-51
9. Rabiner LR (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 77(2):257-286
10. Scheffer T, Decomain C, Wrobel S (2001) Active hidden Markov models for information extraction. In: Lecture notes in computer science, vol 2189. Springer, Berlin, pp 309-318
11. Scheffer T, Wrobel S, Popov B, Ognianov D, Decomain C, Hoche S (2001) Learning hidden Markov models for information extraction actively from partially labeled text. Technical report, University of Magdeburg
12. Seymore K, Mccallum A, Rosenfeld R (1999) Learning hidden Markov model structure for information extraction. In: AAAI 99 workshop on machine learning for information extraction
13. Viterbi AJ (1967) Error bounds for convolutional codes and an asymptotically optimal decoding algorithm. IEEE Trans Inf Theory IT-13 (3):260-269