K-HOG Unsupervised Keyframe Identifier (K-HUKI): Extracting action-rich frames with HOG Features and Unsupervised Learning Article Swipe

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Abhishek Saurabh , Ayush Aggrawal , Saurav Gupta ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.21203/rs.3.rs-6567616/v1

This Report proposes a pioneering method for keyframe identification in activity interpretation. It seamlessly integrates HOG features for informative representation and the flexibility of unsupervised learning through K-means clustering. This approach, named K-HUKI, is further empowered by a robust architecture combining 3D-CNNs for capturing temporal and spatial information and GRUs for handling perpetual dependencies. Extensive evaluation on the UCF101 dataset demonstrates a remarkable improvement in accuracy. By identifying action-rich frames at exceptional speed (almost 5-fold) compared to CNN based approach's and achieving unparalleled accuracy, K-HUKI establishes itself as a groundbreaking advancement in keyframe detection.

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Artificial Intelligence

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Artificial intelligence Unsupervised learning Computer science Pattern recognition (psychology) Identifier Action (physics) Physics Quantum mechanics Programming language

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Type: preprint
Language: en
Landing Page: https://doi.org/10.21203/rs.3.rs-6567616/v1
PDF: https://www.researchsquare.com/article/rs-6567616/latest.pdf
OA Status: gold
References: 32
Related Works: 10
OpenAlex ID: https://openalex.org/W4410070582

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OpenAlex ID: https://openalex.org/W4410070582

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DOI: https://doi.org/10.21203/rs.3.rs-6567616/v1

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Title: K-HOG Unsupervised Keyframe Identifier (K-HUKI): Extracting action-rich frames with HOG Features and Unsupervised Learning

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-05-05

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Authors: Abhishek Saurabh, Ayush Aggrawal, Saurav Gupta

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Landing page: https://doi.org/10.21203/rs.3.rs-6567616/v1

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PDF URL: https://www.researchsquare.com/article/rs-6567616/latest.pdf

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Concepts: Artificial intelligence, Unsupervised learning, Computer science, Pattern recognition (psychology), Identifier, Action (physics), Physics, Quantum mechanics, Programming language

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