DTIC ADA620534: Assessment Of Vision-Based Target Detection And Classification Solutions Using An Indoor Aerial Robot - Info and Reading Options
By Defense Technical Information Center
"DTIC ADA620534: Assessment Of Vision-Based Target Detection And Classification Solutions Using An Indoor Aerial Robot" and the language of the book is English.
“DTIC ADA620534: Assessment Of Vision-Based Target Detection And Classification Solutions Using An Indoor Aerial Robot” Metadata:
- Title: ➤ DTIC ADA620534: Assessment Of Vision-Based Target Detection And Classification Solutions Using An Indoor Aerial Robot
- Author: ➤ Defense Technical Information Center
- Language: English
Edition Identifiers:
- Internet Archive ID: DTIC_ADA620534
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"DTIC ADA620534: Assessment Of Vision-Based Target Detection And Classification Solutions Using An Indoor Aerial Robot" Description:
The Internet Archive:
The role of unmanned aerial vehicles (UAVs) in military, commercial and recreational applications is continuously evolving as developments in technology increase capabilities. The research herein presents an inexpensive computer-vision-based solution for detection and classification of a stationary target with a mobile aerial sensor as a prototyping platform. The main goal of this system is to use commercial-off-the-shelf and open-source components to reduce design complexity to provide a legacy product for future development of specific capabilities. Color imagery collected during flight using a low-resolution camera is used to test the application of a simple algorithm against a commercially available and low cost sensor. Original image processing algorithms that leverage the existing body of works in the open-source community are developed and tested within the Systems Engineering construct. System architecture leverages a modular approach that can be easily modified and adapted to changing requirements and objectives. Conclusions are drawn and recommendations for further study and system development are presented.
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- Internet Archive Link: Archive.org page
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- Number of Files: 16
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- Added Date: 2018-11-01 22:33:35
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