MPEG-7 visual motion descriptors

Jeannin, S.; Divakaran, Ajay

doi:10.1109/76.927428

Cited by 148 publications

(86 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The MPEG-7 [1] motion activity descriptor attempts to capture human perception of the "intensity of action" or the "pace" of a video segment. For instance, a goal scoring moment in a soccer game would be perceived as a "high action" sequence by most human viewers.…”

Section: Motion Activity Descriptormentioning

confidence: 99%

See 1 more Smart Citation

Video Summarization Using Mpeg-7 Motion Activity and Audio Descriptors

et al. 2003

View full text Add to dashboard Cite

We present video summarization and indexing techniques using the MPEG-7 motion activity descriptor. The descriptor can be extracted in the compressed domain and is compact, and hence is easy to extract and match. We establish that the intensity of motion activity of a video shot is a direct indication of its summarizability. We describe video summarization techniques based on sampling in the cumulative motion activity space. We then describe combinations of the motion activity based techniques with generalized sound recognition that enable completely automatic generation of news and sports video summaries. Our summarization is computationally simple and flexible, which allows rapid generation of a summary of any desired length.This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved. {ajayd,peker,regu,zxiong,romain}@merl.com AbstractWe present video summarization and indexing techniques using the MPEG-7 motion activity descriptor. The descriptor can be extracted in the compressed domain and is compact, and hence is easy to extract and match. We establish that the intensity of motion activity of a video shot is a direct indication of its summarizability. We describe video summarization techniques based on sampling in the cumulative motion activity space. We then describe combinations of the motion activity based techniques with generalized sound recognition that enable completely automatic generation of news and sports video summaries. Our summarization is computationally simple and flexible, which allows rapid generation of a summary of any desired length.

show abstract

Section: Motion Activity Descriptormentioning

confidence: 99%

“…In this chapter we present a novel approach to video summarization using the MPEG-7 motion activity descriptor [1]. Since our motivation is computational simplicity and easy incorporation into consumer system hardware, we focus on feature extraction in the compressed domain.…”

Section: Introductionmentioning

confidence: 99%

Video Summarization Using Mpeg-7 Motion Activity and Audio Descriptors

et al. 2003

View full text Add to dashboard Cite

show abstract

“…Motion Activity considers the intensity, direction, spatial distribution and temporal distribution of activity in a video sequence. To calculate the motion activity, according to [27], the standard deviation of the magnitudes of all motion vectors of each frame has been quantized between 1 and 5, and the average of the quantized motion activity values over all the frames has been used as the Motion Activity of each video sequence.…”

Section: B Selecting Source Video Sequencesmentioning

confidence: 99%

An Anatomy of SVC for Full HD Video Streaming

Zakerinasab

Wang

2014

2014 IEEE 22nd International Symposium on Modelling, Analysis &Amp; Simulation of Computer and Telecommunication Systems

View full text Add to dashboard Cite

Abstract-The continuous developments and improvements of network infrastructure along with the growing number of modern smartphones, tablets and smart TVs have led to an increasing popularity of multimedia applications, such as video conferencing, video streaming and mobile TV. Towards delivering video stream to diverse devices over a heterogamous network, scalable video coding (SVC) has received many research attentions. SVC is an extension of H.264/AVC that allows a video streaming service provider to encode a high quality video into a number of scalable layers. The receivers of the stream may decode the video at the appropriate quality level that is suitable for their hardware/software capabilities and network connections. Nevertheless, compared to single layer H.264/AVC, the de facto standard for many commercial streaming service providers such as YouTube, SVC is not widely deployed, mostly due to its overhead in terms of bitrate and complexity. In this paper, we conduct a thorough study on the performance of SVC for full HD video streaming. Our performance analysis identifies good and bad uses of SVC, quantifies the coding overhead, and benchmarks the SVC video quality under different spatial, temporal, and quality settings. Through the use a set of carefully selected and diverse video sequences, we also identify the types of video that can benefit from SVC.

show abstract

“…As motion provides one of the easiest cues to a sequence's temporal dimension [1], it is one of the most important visual features for content-based video representation and is increasingly becoming an essential part of several applications, including contentbased video indexing for browsing and retrieval [2], [3], video surveillance systems [4], video object segmentation and tracking [3]. Amongst these different applications, one of the most interesting is using object motion in video indexing for accessing large amounts of multimedia data over the Internet.…”

Section: Introductionmentioning

confidence: 99%

Filtering of Block Motion Vectors for Use in Motion-Based Video Indexing and Retrieval

Sorwar

Murshed

2005

IEICE Transactions on Fundamentals of Electronics, Communicatio

View full text Add to dashboard Cite

SUMMARYThough block-based motion estimation techniques are primarily designed for video coding applications, they are increasingly being used in other video analysis applications due to their simplicity and ease of implementation. The major drawback associated with these techniques is that noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors. Similar noises may further be introduced when the technique of global motion compensation is applied to obtain true object motion from video sequences where both the camera and object motions are present. This paper presents a new technique for capturing large number of true object motion vectors by eliminating the false motion vector fields, for use in the application of object motion based video indexing and retrieval applications. Experimental results prove that our proposed technique significantly increases the percentage of retained true object motion vectors while eliminating all false motion vectors for variety of standard and non-standard video sequences.

show abstract

MPEG-7 visual motion descriptors

Cited by 148 publications

References 18 publications

Video Summarization Using Mpeg-7 Motion Activity and Audio Descriptors

Video Summarization Using Mpeg-7 Motion Activity and Audio Descriptors

An Anatomy of SVC for Full HD Video Streaming

Filtering of Block Motion Vectors for Use in Motion-Based Video Indexing and Retrieval

Contact Info

Product

Resources

About