A survey on compressed domain video analysis techniques

Babu, Venkatesh R and Tom, Manu and Wadekar, Paras (2016) A survey on compressed domain video analysis techniques. In: MULTIMEDIA TOOLS AND APPLICATIONS, 75 (2). pp. 1043-1078.

PDF Mul_Too_App_75-2_1043_2016.pdf - Published Version Restricted to Registered users only Download (2MB) | Request a copy

Abstract

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

Item Type:	Journal Article
Publication:	MULTIMEDIA TOOLS AND APPLICATIONS
Publisher:	SPRINGER
Additional Information:	Copy right for this article belongs to the SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
Keywords:	Video object segmentation; Human action recognition; Indexing; Retrieval; Face detection; Video classification; Object tracking; Object localization; Moving object detection; H.264/AVC; HEVC; MPEG; Compressed domain; Quantization parameter; Motion vectors; Transform coefficients; Video analysis
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	29 Feb 2016 07:13
Last Modified:	29 Feb 2016 07:13
URI:	http://eprints.iisc.ac.in/id/eprint/53325

Actions (login required)

View Item