Version 1
: Received: 19 August 2023 / Approved: 22 August 2023 / Online: 22 August 2023 (09:38:49 CEST)
Version 2
: Received: 2 September 2023 / Approved: 4 September 2023 / Online: 5 September 2023 (05:17:43 CEST)
How to cite:
Ahmed, M.; Aqib, M. Towards the Development of A Low-Cost Solution for Wildlife Tracking using An Unmanned Aerial Platform. Preprints2023, 2023081533. https://doi.org/10.20944/preprints202308.1533.v2
Ahmed, M.; Aqib, M. Towards the Development of A Low-Cost Solution for Wildlife Tracking using An Unmanned Aerial Platform. Preprints 2023, 2023081533. https://doi.org/10.20944/preprints202308.1533.v2
Ahmed, M.; Aqib, M. Towards the Development of A Low-Cost Solution for Wildlife Tracking using An Unmanned Aerial Platform. Preprints2023, 2023081533. https://doi.org/10.20944/preprints202308.1533.v2
APA Style
Ahmed, M., & Aqib, M. (2023). Towards the Development of A Low-Cost Solution for Wildlife Tracking using An Unmanned Aerial Platform. Preprints. https://doi.org/10.20944/preprints202308.1533.v2
Chicago/Turabian Style
Ahmed, M. and Muhammad Aqib. 2023 "Towards the Development of A Low-Cost Solution for Wildlife Tracking using An Unmanned Aerial Platform" Preprints. https://doi.org/10.20944/preprints202308.1533.v2
Abstract
Owing to the upsurge in the number of endangered species and understanding animal patterns in general as well as population demographics; the monitoring of wildlife species is an essential for the conservation and safety of animals. In order to organize and manage the reserves, the nature bequeaths to us, we need to have hands-on information of their population and food trends, conditions where they survive and other species in the ecosystem. The paper presents a vision-based approach to monitor wildlife using an aerial platform. A quad-rotor based aerial platform is used for the very first time for this purpose. Field imaging is done using a digital cellphone camera mounted on the platform to acquire video of horses in the field. Two techniques, Lucas-Kanade and Horn-Schunck methods are applied on the acquired set of images and the results are compared. Noise due to fluctuations and light conditions are minimized using Gaussian and HSV filters. Experiments show results with an absolute mean difference of 2.84 pixels and 8.50 pixels for changes in X and Y directions respectively for the two approaches.
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Mansoor Ahmed
Commenter's Conflict of Interests: Author