Research Inferences In Video Compression Domain
K.N. Abdul Kader Nihal
K.N. Abdul Kader Nihal, Assistant Professor, PG & Research Department of Computer Science, Jamal Mohamed College, Tiruchirappalli, (Tamil Nadu), India.
Manuscript received on February 03, 2019. | Revised Manuscript received on February 14, 2019. | Manuscript published on August 30, 2019. | PP: 3659-3665 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9370088619/19©BEIESP | DOI: 10.35940/ijeat.F9370.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Video Compression (VC) is a painstaking investigation area in the modernization of digital existence because of more evolution being emerged in web relevance. In this direction, video compression is grown-up rapdily and confirmed by the large number of myriad applications in Video streaming, Computer Vision like Video Tampering Detection, Video Surveillance and Camera Moving etc., which collectively use of this compression technology. This paper attributes opens-up endeav ours the whole possible and recent research directions and its challenges by focusing the potential investigations on compression domain of MPEG, H.264, H.265 compression coding standard with latest computing techniques in learning videos via Machine Learning.
Keywords: Video Compression, Computer Vision, Applications, Human Actions, Video Indexing & Retrieval, Object Tracking, Moving Object Detection & Segmentation, Dominant Flow & Face Detection, Next-gen VC.