SELECTED SINGLE FACE TRACKING IN TECHNICALLY CHALLENGING DIFFERENT BACKGROUND VIDEO SEQUENCES USING COMBINED FEATURES
| Autor: | A.S. Sharan, Y.P. Gowramma, S. Ranganatha, G.N. Karthik |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Facial motion capture Computer science Different Background Combined Features ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Video sequence 02 engineering and technology lcsh:Computer applications to medicine. Medical informatics 01 natural sciences Video Sequences KLT lcsh:Telecommunication lcsh:TK5101-6720 Track Human Face 0103 physical sciences 0202 electrical engineering electronic engineering information engineering lcsh:R858-859.7 020201 artificial intelligence & image processing Computer vision Artificial intelligence 010306 general physics business |
| Zdroj: | ICTACT Journal on Image and Video Processing, Vol 9, Iss 2, Pp 1911-1918 (2018) |
| ISSN: | 0976-9102 0976-9099 |
| DOI: | 10.21917/ijivp.2018.0271 |
| Popis: | The commonly identified limitations of video face trackers are, the inability to track human face in different background video sequences with the conditions like occlusion, low quality, abrupt motions and failing to track single face when it contain multiple faces. In this paper, we propose a novel algorithm to track human face in different background video sequences with the conditions listed above. The proposed algorithm describes an improved KLT tracker. We collect Eigen, FAST as well as HOG features and combine them together. The combined features are given to the tracker to track the face. The algorithm being proposed is tested on challenging datasets videos and measured for performance using the standard metrics. |
| Databáze: | OpenAIRE |
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