Recognition of Human Emotion Detection and Annotation, using Local Descriptor and Support Vector Machine
Shama P S1, Pattan Prakash2

1Shama P S*, Computer Science & Engineering, PDACE, Kalaburagi,Karnataka, India.
2Dr.Pattan Prakash, Computer Science & Engineering, PDACE, Kalaburagi, Karnataka, India

Manuscript received on November 14, 2019. | Revised Manuscript received on 25 November, 2019. | Manuscript published on December 10, 2019. | PP: 2838-2843 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7201129219/2019©BEIESP | DOI: 10.35940/ijitee.B7201.129219
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Abstract: 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. 
Keywords: People Detection, Segmentation, Recognition and Emotion Annotation.
Scope of the Article: Pattern Recognition