Detection of Gradual Transition in Videos

Bhaumik, Hrishikesh; Chakraborty, Manideepa; Bhattacharyya, Siddhartha; Chakraborty, Susanta Kumar

doi:10.4018/978-1-5225-0498-6.ch011

Cited by 5 publications

(5 citation statements)

References 59 publications

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“…Its aim is to build cost function based on fuzzy rule to optimize the objectives. In this algorithm, network lifetime of the network increased, and any change in topology can relearned by using generated rule of fuzzy logic [12].…”

Section: Related Workmentioning

confidence: 99%

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Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy

Zhang

Liao

2021

Complexity

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The application of machine learning touches all activities of human behavior such as computer network and routing packets in LAN. In the field of our research here, emphasis was placed on extracting weights that would affect the speed of the network's response and finding the best path, such as the number of nodes in the path and the congestion on each path, in addition to the cache used for each node. Therefore, the use of these elements in building the neural network is worthy, as is the exploitation of the feed forwarding and the backpropagation in the neural network in order to reach the best prediction for the best path. The goal of the proposed neural network is to minimize the network time delay within the optimization of the packet paths being addressed in this study. The shortest path is considered as the key issue in routing algorithm that can be carried out with real time of path computations. Exploiting the gaps in previous studies, which are represented in the lack of training of the system and the inaccurate prediction as a result of not taking into consideration the hidden layers' feedback, leads to great performance. This study aims to suggest an efficient algorithm that could help in selecting the shortest path to improve the existing methods using weights derived from packet ID and to change neural network iteration simultaneously. In this study, the design of the efficient neural network of appropriate output is discussed in detail including the principles of the network. The findings of the study revealed that exploiting the power of computational system to demonstrate computer simulation is really effective. It is also shown that the system achieved good results when training the neural network system to get 2.4% time delay with 5 nodes in local LAN. Besides, the results showed that the major features of the proposed model will be able to run in real time and are also adaptive to change with path topology.

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Section: Related Workmentioning

confidence: 99%

“…Chromosome group called population was used to perform solution for specified problem. is algorithm uses value fitness to illustrate the quality of chromosome as problem needed [12]. When chromosome has high fitness value, then this path is the optimal one.…”

Section: Related Workmentioning

confidence: 99%

Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy

Zhang

Liao

2021

Complexity

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“…Bhaumik et al [ 143 ] proposed a method to detect dissolve transitions by utilizing two stages. In the first stage, the candidate transitions were distinguished by recognizing the parabolic patterns generated by the fuzzy entropy of the frames.…”

Section: Sbd Approachesmentioning

confidence: 99%

Methods and Challenges in Shot Boundary Detection: A Review

Abdulhussain

Ramli

Saripan

et al. 2018

Entropy

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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.

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“…For statistics-based approaches, properties such as the mean, median, and standard deviation are often used. There are some other SBD approaches, such as the temporal slice coherency [44], fuzzy rules [45], and two-phased [46] approaches. Due to deep learning having become a hot topic in research work, deep-learning-based approaches have been increasingly applied to SBD works [47][48][49][50].…”

Section: Sbd Approachesmentioning

confidence: 99%

“…Two-phased Bhaumik [46] The first phase detects candidate dissolves by identifying parabolic patterns in the mean fuzzy entropy of the frames. The second phase uses a filter to eliminate candidates based on thresholds set for each of the four stages of filtration.…”

Section: Fuzzy-rule-basedmentioning

confidence: 99%

Video Searching and Fingerprint Detection by Using the Image Query and PlaceNet-Based Shot Boundary Detection Method

Jiang

Kim

2018

Applied Sciences

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This work presents a novel shot boundary detection (SBD) method based on the Place-centric deep network (PlaceNet), with the aim of using video shots and image queries for video searching (VS) and fingerprint detection. The SBD method has three stages. In the first stage, we employed Local Binary Pattern-Singular Value Decomposition (LBP-SVD) features for candidate shot boundaries selection. In the second stage, we used the PlaceNet to select the shot boundary by semantic labels. In the third stage, we used the Scale-Invariant Feature Transform (SIFT) descriptor to eliminate falsely detected boundaries. The experimental results show that our SBD method is effective on a series of SBD datasets. In addition, video searching experiments are conducted by using one query image instead of video sequences. The results under several image transitions by using shot fingerprints have shown good precision.

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Detection of Gradual Transition in Videos

Cited by 5 publications

References 59 publications

Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy

Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy

Methods and Challenges in Shot Boundary Detection: A Review

Video Searching and Fingerprint Detection by Using the Image Query and PlaceNet-Based Shot Boundary Detection Method

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