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HMM Classifier for Human Activity Recognition
| Content Provider | Semantic Scholar |
|---|---|
| Author | Gaikwad, Kanchan |
| Copyright Year | 2012 |
| Abstract | The rapid improvement in technology causes more attention towards to Recognizing of human activities from video. These new technological growth has made vision-based research much moreinteresting and efficient than ever before. This paper present novel HMM (Hidden Markov Model) based approach for Human activity recognition from video. There are different approaches of HMM to recognize action of human from video. Like threshold and voting to automatically and effectively segment and recognize complex activities, segment and recognize complex activities and for simple activities we useElman Network (EN) and two hybrids of Neural Network (NN) and HMM, i.e. HMM -NN and NN-HMM. |
| Starting Page | 27 |
| Ending Page | 36 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| DOI | 10.5121/cseij.2012.2403 |
| Volume Number | 2 |
| Alternate Webpage(s) | http://www.airccse.org/journal/cseij/papers/2412cseij03.pdf |
| Alternate Webpage(s) | http://airccse.org/journal/cseij/papers/2412cseij03.pdf |
| Alternate Webpage(s) | https://doi.org/10.5121/cseij.2012.2403 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
