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Dronecaps : recognition of human actions in drone videos using capsule networks with binary volume comparisons
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Algamdi, Abdullah M., Sanchez Silva, Victor and Li, Chang-Tsun (2020) Dronecaps : recognition of human actions in drone videos using capsule networks with binary volume comparisons. In: 27th IEEE International Conference on Image Processing, Abu Dhabi, 25-28 Oct 2020. Published in: IEEE International Conference on Image Processing ICIP 2020 (In Press)
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Abstract
Understanding human actions from videos captured by drones is a challenging task in computer vision due to the unfamiliar viewpoints of individuals and changes in their size due to the camera’s location and motion. This work proposes DroneCaps, a capsule network architecture for multi-label human action recognition (HAR) in videos captured by drones. DroneCaps uses features computed by 3D convolution neural networks plus a new set of features computed by a novel Binary Volume Comparison layer. All these features, in conjunction with the learning power of CapsNets, allow understanding and abstracting the different viewpoints and poses of the depicted individuals very efficiently, thus improving multi-label HAR. The evaluation of the DroneCaps architecture’s performance for multi-label classification shows that it outperforms state-of-the-art methods on the Okutama-Action dataset.
| Item Type: | Conference Item (Speech) | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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| Divisions: | Faculty of Science > Computer Science | ||||||||
| Library of Congress Subject Headings (LCSH): | Drone aircraft , Drone aircraft in remote sensing, Computer vision , Pattern recognition system, Human activity recognition , Computer network architectures , Three-dimensional imaging , Neural networks (Computer science) , Adaptive routing (Computer network management) | ||||||||
| Journal or Publication Title: | IEEE International Conference on Image Processing ICIP 2020 | ||||||||
| Publisher: | IEEE | ||||||||
| Official Date: | 2020 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 16 September 2020 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | In Press | ||||||||
| Publisher Statement: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Copyright Holders: | IEEE | ||||||||
| Conference Paper Type: | Speech | ||||||||
| Title of Event: | 27th IEEE International Conference on Image Processing | ||||||||
| Type of Event: | Conference | ||||||||
| Location of Event: | Abu Dhabi | ||||||||
| Date(s) of Event: | 25-28 Oct 2020 | ||||||||
| Related URLs: |
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