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2021 | OriginalPaper | Chapter

Fast Hand Detection in Collaborative Learning Environments

Authors : Sravani Teeparthi, Venkatesh Jatla, Marios S. Pattichis, Sylvia Celedón-Pattichis, Carlos LópezLeiva

Published in: Computer Analysis of Images and Patterns

Publisher: Springer International Publishing

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Abstract

Long-term object detection requires the integration of frame-based results over several seconds. For non-deformable objects, long-term detection is often addressed using object detection followed by video tracking. Unfortunately, tracking is inapplicable to objects that undergo dramatic changes in appearance from frame to frame. As a related example, we study hand detection over long video recordings in collaborative learning environments. More specifically, we develop long-term hand detection methods that can deal with partial occlusions and dramatic changes in appearance.

Our approach integrates object-detection, followed by time projections, clustering, and small region removal to provide effective hand detection over long videos. The hand detector achieved average precision (AP) of \(72\%\) at 0.5 intersection over union (IoU). The detection results were improved to \(81\%\) by using our optimized approach for data augmentation. The method runs at 4.7\(\times \) the real-time with AP of \(81\%\) at 0.5 intersection over the union. Our method reduced the number of false-positive hand detections by 80\(\%\) by improving IoU ratios from 0.2 to 0.5. The overall hand detection system runs at 4\(\times \) real-time.

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Title: Fast Hand Detection in Collaborative Learning Environments
Authors: Sravani Teeparthi
Venkatesh Jatla
Marios S. Pattichis
Sylvia Celedón-Pattichis
Carlos LópezLeiva
Publisher: Springer International Publishing
Book: Computer Analysis of Images and Patterns
Print ISBN: 978-3-030-89127-5

Electronic ISBN: 978-3-030-89128-2

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-89128-2_43

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