ALMEGA-VIR: face video retrieval system

Prathiba, T.; Kumari, R. Shantha Selva; Selvi, M. Chengathir

doi:10.1080/13682199.2023.2225372

The Imaging Science Journal

2023

DOI: 10.1080/13682199.2023.2225372

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ALMEGA-VIR: face video retrieval system

T. Prathiba¹,

R. Shantha Selva Kumari²,

M. Chengathir Selvi³

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2023

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An Efficient Video Frames Retrieval System Using Speeded Up Robust Features Based Bag of Visual Words

Hussain

2023

ADCAIJ

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Most studies in content-based image retrieval (CBIR) systems use database images of multiple classes. There is a lack of an automatic video frame retrieval system based on the query image. Low-level features i.e., the shape and colors of most of the objects are almost the same e.g., the sun and an orange are both round and red in color. Features such as speeded up robust features (SURF) used in most of the content-based video retrieval (CBVR) & CBIR research work are non-invariant features which may affect the overall accuracy of the CBIR system. The use of a simple and weak classifier or matching technique may also affect the accuracy of the CBIR system on high scale. The unavailability of datasets for content-based video frames retrieval is also a research gap to be explored in this paper.

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An Efficient Video Frames Retrieval System Using Speeded Up Robust Features Based Bag of Visual Words

Hussain

2023

ADCAIJ

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ALMEGA-VIR: face video retrieval system

Cited by 1 publication

References 62 publications

An Efficient Video Frames Retrieval System Using Speeded Up Robust Features Based Bag of Visual Words

An Efficient Video Frames Retrieval System Using Speeded Up Robust Features Based Bag of Visual Words

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