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A Framework for Human Activity Recognition using Pose Feature for Video Surveillance System
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kushwaha, Alok Kumar Singh Srivastava, Rajeev |
| Copyright Year | 2016 |
| Abstract | In this paper, a system framework has been presented to recognize a human activity recognition approach. The proposed framework is composed of three consecutive modules: (i) detecting and locating people by background subtraction, (ii) scale invariant contour-based pose features from silhouettes (iii) finally classifying activities of people by Multiclass Support vector machine (SVM) classifier. The proposed method use approximate median filter based background–foreground separation technique to extract motion information and generate object silhouettes to activity of humans present in a scene monitored by a camera. Experimental results demonstrate that the proposed method can recognize these activities accurately for standard KTH database. |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.ijcaonline.org/proceedings/ngtbes2016/number1/25540-3502?format=pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
