Video shot boundary detection using multiscale geometric analysis of nsct and least squares support vector machine

Mondal, Jaydeb; Kundu, Malay K.; Das, Susmita; Chowdhury, Manish

doi:10.1007/s11042-017-4707-9

Cited by 26 publications

(19 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TRECVid contains many subsets of video test data and ground truth information targeting the shot boundary detection which are widely used to evaluate the performance of different shot boundary detection algorithms [33]. Significant advancements are made by [34], [35], [36], [37], [38] [39], [40] to perform shot boundary detection to achieve optimal accuracy. Different accuracy ranges have been reported on TRECVid dataset from 94% to 96%.…”

Section: Related Workmentioning

confidence: 99%

Content-based Automatic Video Genre Identification

Shamsi¹,

Daudpota²,

Shaikh³

2019

IJACSA

View full text Add to dashboard Cite

Video content is evolving enormously with the heavy usage of internet and social media websites. Proper searching and indexing of such video content is a major challenge. The existing video search potentially relies on the information provided by the user, such as video caption, description and subsequent comments on the video. In such case, if users provide insufficient or incorrect information about the video genre, the video may not be indexed correctly and ignored during search and retrieval. This paper proposes a mechanism to understand the contents of video and categorize it as Music Video, Talk Show, Movie/Drama, Animation and Sports. For video classification, the proposed system uses audio and visual features like audio signal energy, zero crossing rate, spectral flux from audio and shot boundary, scene count and actor motion from video. The system is tested on popular Hollywood, Bollywood and YouTube videos to give an accuracy of 96%.

show abstract

Section: Related Workmentioning

confidence: 99%

Content-based Automatic Video Genre Identification

Shamsi¹,

Daudpota²,

Shaikh³

2019

IJACSA

View full text Add to dashboard Cite

show abstract

“…Although some algorithms utilize frame skipping, they show a moderate computational cost because of the computation complexity of the features used such as SIFT, SURF, and Harris. Obviously, algorithms that show a high computational cost such as [ 22 , 125 ] gain a remarkable accuracy compared to other algorithms. For [ 125 ], the computational load is due to utilizing local features and motion compensation, and, for [ 22 ], it is due to the number of decomposition levels and local features that are used for each color space.…”

Section: Sbd Approachesmentioning

confidence: 99%

“…That is, SBD algorithm performance can be measured by its ability in detecting correct transition. Where, a SBD accuracy generally depends on the extracted features and their effectiveness of representing the the visual content of video frames [ 22 ]. The second factor that influences a SBD algorithm performance is the computational cost of the algorithm, that need to be reduced where in contrast, algorithm speed is increased.…”

Section: Introductionmentioning

confidence: 99%

Methods and Challenges in Shot Boundary Detection: A Review

Abdulhussain

Ramli

Saripan

et al. 2018

Entropy

View full text Add to dashboard Cite

Abstract:The recent increase in the number of videos available in cyberspace is due to the availability of multimedia devices, highly developed communication technologies, and low-cost storage devices. These videos are simply stored in databases through text annotation. Content-based video browsing and retrieval are inefficient due to the method used to store videos in databases. Video databases are large in size and contain voluminous information, and these characteristics emphasize the need for automated video structure analyses. Shot boundary detection (SBD) is considered a substantial process of video browsing and retrieval. SBD aims to detect transition and their boundaries between consecutive shots; hence, shots with rich information are used in the content-based video indexing and retrieval. This paper presents a review of an extensive set for SBD approaches and their development. The advantages and disadvantages of each approach are comprehensively explored. The developed algorithms are discussed, and challenges and recommendations are presented.

show abstract

“…In many other computer vision tasks, similarity based approaches like identifying person objects are commonly used. For example, in shot boundary detection [8], [9] (SBD), some methods evaluate the The associate editor coordinating the review of this manuscript and approving it for publication was Jinjia Zhou . similarity distances between two selected consecutive video frames to detect the shot transitions [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

Scale Voting With Pyramidal Feature Fusion Network for Person Search

Hong

Liu

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Person search aims to find the target person among a large gallery set of real scene images. Candidates should be detected and cropped before recognizing their identifications. The detection process results in a great variance of object image scales. To address this we propose Pyramidal Feature Fusion Network that integrates the top-down mid-level features to provide multi-level feature outputs. Furthermore, we propose to apply each of the mid-level features independently in ranking and we design a ranking algorithm named Scale Voting that votes among these ranking results from different feature levels to get the final ranking order. In this approach, we can make better use of the diversity and consistency information that is hidden in different mid-levels of features. The proposed algorithm achieves the state-of-the-art performance on prevalent person search datasets.INDEX TERMS Person search, scale voting, pyramidal feature fusion network.

show abstract

Video shot boundary detection using multiscale geometric analysis of nsct and least squares support vector machine

Cited by 26 publications

References 21 publications

Content-based Automatic Video Genre Identification

Content-based Automatic Video Genre Identification

Methods and Challenges in Shot Boundary Detection: A Review

Scale Voting With Pyramidal Feature Fusion Network for Person Search

Contact Info

Product

Resources

About