Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/3252
Title: | Camera Zoom Motion Detection in the Compressed Domain |
Authors: | Sandula, Pavan Okade, Manish |
Keywords: | Zoom motion Local tetra patterns Uniform patterns Camera motion C-SVM |
Issue Date: | Feb-2019 |
Publisher: | IEEE |
Citation: | International Conference on Range Technology (ICORT-2019), Chandipur, India, 15-17 February,2019. |
Abstract: | In this paper we investigate the application of local tetra patterns to the compressed domain camera zoom recognition problem. The primary aim is to separate the zooming frames from the non-zooming (panning, tilting) frames for which the block motion vector orientation information is modeled utilizing a 3× 3 neighborhood and local tetra patterns. These patterns are binarized followed by feature reduction using the concept of uniform patterns and finally fed to the C-SVM classifier for recognition purposes. Comparative analysis with state-ofthe-art methods using ESME and H.264 obtained block motion vectors extracted from standard video sequences show superior performance for the proposed method. |
Description: | Copyright of this document belongs to proceedings publisher. |
URI: | http://hdl.handle.net/2080/3252 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2019_ICORT_MOkade_Camera.pdf | Paper | 179.79 kB | Adobe PDF | View/Open |
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