Recognition of Human Emotion Detection and Annotation, using Local Descriptor and Support Vector Machine
In multimedia data analysis, video tagging is the most challenging and active research area. In which finding or detecting the object with the dynamic environment is most challenging. Object detection and its validation are an essential functional step in video annotation. Considering the above chal...
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| Published in: | International journal of innovative technology and exploring engineering Vol. 9; no. 2; pp. 2838 - 2843 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
30.12.2019
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| ISSN: | 2278-3075, 2278-3075 |
| Online Access: | Get full text |
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| Summary: | In multimedia data analysis, video tagging is the most challenging and active research area. In which finding or detecting the object with the dynamic environment is most challenging. Object detection and its validation are an essential functional step in video annotation. Considering the above challenges, the proposed system designed to presents the people detection module from a complex background. Detected persons are validated for further annotation process. Using publically available dataset for module design, Viola-Jones object detection algorithm is used for person detection. Support Vector Machine (SVM) authenticate the detected object/person based on it local features using Local Binary Pattern (LBP). The performance of the proposed system presents given architecture is effectively annotating the detected people emotion. |
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| ISSN: | 2278-3075 2278-3075 |
| DOI: | 10.35940/ijitee.B7201.129219 |