A survey on compressed domain video analysis techniques
| Autor: | Manu Tom, R. Venkatesh Babu, Paras Wadekar |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Pixel
Computer Networks and Communications Computer science business.industry Quantization (signal processing) Search engine indexing ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology Hardware and Architecture Video tracking 0202 electrical engineering electronic engineering information engineering Media Technology 020201 artificial intelligence & image processing Computer vision Segmentation Artificial intelligence Quantization (image processing) Face detection business Software Data compression |
| Zdroj: | Multimedia Tools and Applications. 75:1043-1078 |
| ISSN: | 1573-7721 1380-7501 |
| DOI: | 10.1007/s11042-014-2345-z |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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