Open AccessRecognition of Human Emotion Detection and Annotation, using Local Descriptor and Support Vector Machine
Author(s) -
Shama P S*,
Divya Prakash
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b7201.129219
Subject(s) - support vector machine , local binary patterns , annotation , computer science , artificial intelligence , object (grammar) , object detection , process (computing) , pattern recognition (psychology) , viola–jones object detection framework , computer vision , machine learning , histogram , image (mathematics) , face detection , facial recognition system , operating system
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.