What question did this study set out to answer?

To review the algorithmic development, capabilities, and persistent technical challenges in automated shot boundary detection for content-based video indexing and retrieval.

March 23, 2018EntropyOpen Access

Methods and Challenges in Shot Boundary Detection: A Review

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Authors

SASadiq H. Abdulhussain ARAbd Rahman Ramli MSM. Iqbal Saripan

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Overview

Comprehensive review reveals algorithmic approaches and key challenges in video shot boundary detection, highlighting critical improvements needed for content-based multimedia retrieval.

Key Points

To review the algorithmic development, capabilities, and persistent technical challenges in automated shot boundary detection for content-based video indexing and retrieval.
Surveyed and evaluated an extensive collection of shot boundary detection algorithms and their developmental progression.
Assessed the comparative advantages, limitations, and operational trade-offs across various transition detection methodologies in video databases.
Automated detection of transitions between consecutive video shots provides foundational, information-rich segments necessary to replace inefficient text-annotation storage.
Current shot boundary detection algorithms encounter substantial hurdles in managing complex visual transitions across massive multimedia datasets, requiring standardized benchmarks and improved computational efficiency.

Cite This Study

Abdulhussain et al. (2018) studied this question.

synapsesocial.com/papers/69d8e6ea13e0539d74bedef9 https://doi.org/10.3390/e20040214

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March 23, 2018EntropyOpen Access

Methods and Challenges in Shot Boundary Detection: A Review

View Full Paper

Ask AI

Bookmark

Authors

SASadiq H. Abdulhussain ARAbd Rahman Ramli MSM. Iqbal Saripan

Discussion

Member takes

Overview

Comprehensive review reveals algorithmic approaches and key challenges in video shot boundary detection, highlighting critical improvements needed for content-based multimedia retrieval.

Key Points

To review the algorithmic development, capabilities, and persistent technical challenges in automated shot boundary detection for content-based video indexing and retrieval.
Surveyed and evaluated an extensive collection of shot boundary detection algorithms and their developmental progression.
Assessed the comparative advantages, limitations, and operational trade-offs across various transition detection methodologies in video databases.
Automated detection of transitions between consecutive video shots provides foundational, information-rich segments necessary to replace inefficient text-annotation storage.
Current shot boundary detection algorithms encounter substantial hurdles in managing complex visual transitions across massive multimedia datasets, requiring standardized benchmarks and improved computational efficiency.

Cite This Study

Abdulhussain et al. (2018) studied this question.

synapsesocial.com/papers/69d8e6ea13e0539d74bedef9 https://doi.org/10.3390/e20040214

View Full Paper

Ask AI

Bookmark