Video Scene Detection Using Compact Bag of Visual Word Models
Joint Authors
Haroon, Muhammad
Baber, Junaid
Ullah, Ihsan
Daudpota, Sher Muhammad
Bakhtyar, Maheen
Devi, Varsha
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-08
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Video segmentation into shots is the first step for video indexing and searching.
Videos shots are mostly very small in duration and do not give meaningful insight of the visual contents.
However, grouping of shots based on similar visual contents gives a better understanding of the video scene; grouping of similar shots is known as scene boundary detection or video segmentation into scenes.
In this paper, we propose a model for video segmentation into visual scenes using bag of visual word (BoVW) model.
Initially, the video is divided into the shots which are later represented by a set of key frames.
Key frames are further represented by BoVW feature vectors which are quite short and compact compared to classical BoVW model implementations.
Two variations of BoVW model are used: (1) classical BoVW model and (2) Vector of Linearly Aggregated Descriptors (VLAD) which is an extension of classical BoVW model.
The similarity of the shots is computed by the distances between their key frames feature vectors within the sliding window of length L, rather comparing each shot with very long lists of shots which has been previously practiced, and the value of L is 4.
Experiments on cinematic and drama videos show the effectiveness of our proposed framework.
The BoVW is 25000-dimensional vector and VLAD is only 2048-dimensional vector in the proposed model.
The BoVW achieves 0.90 segmentation accuracy, whereas VLAD achieves 0.83.
American Psychological Association (APA)
Haroon, Muhammad& Baber, Junaid& Ullah, Ihsan& Daudpota, Sher Muhammad& Bakhtyar, Maheen& Devi, Varsha. 2018. Video Scene Detection Using Compact Bag of Visual Word Models. Advances in Multimedia،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1118403
Modern Language Association (MLA)
Haroon, Muhammad…[et al.]. Video Scene Detection Using Compact Bag of Visual Word Models. Advances in Multimedia No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1118403
American Medical Association (AMA)
Haroon, Muhammad& Baber, Junaid& Ullah, Ihsan& Daudpota, Sher Muhammad& Bakhtyar, Maheen& Devi, Varsha. Video Scene Detection Using Compact Bag of Visual Word Models. Advances in Multimedia. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1118403
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118403