Computer Vision for Object Recognition and Tracking Based on Raspberry Pi
Global Proceedings Repository
View Archive Info| Field | Value | |
| Title |
Computer Vision for Object Recognition and Tracking Based on Raspberry Pi
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| Creator |
Ali A. Abed (SMIEEE)
Sara A. Rahman |
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| Description |
The tasks of object recognition and tracking are a key component of video surveillance and monitoring systems. This paper presents CamShift (Continuously Adaptive Mean Shift) algorithm and color detection in darkness for tracking a target with video sequences in real time. The system described in this paper contains a camera that is connected to a Raspberry Pi. The Raspberry Pi has an image processing algorithm which detects an object first and then tracks it. Color detection generally is a primary stage in most of the image processing applications, if the application is based on the color information. To monitor object in video, an embedded board is adopted to monitor the activity of the object of interest based on Raspberry Pi with LCD touch screen display TFT monitor. A software method for real time implementation of moving object tracking and recognition is done using Python programming language with OpenCV libraries. The two algorithms are tested and compared to prove the robustness of the proposed color detection algorithm operating in a low light environment. Good practical results for recognition and tracking are obtained.
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| Publisher |
Int'l Conference on Change, Innovation, Informatics and Disrurptuive Technology
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| Contributor |
—
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| Date |
2016-12-17 20:54:48
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| Type |
Peer-reviewed Paper
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| Format |
application/pdf
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| Identifier |
http://proceedings.sriweb.org/repository/index.php/ICCIIDT/icciidtt_london/paper/view/22
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| Source |
Int'l Conference on Change, Innovation, Informatics and Disrurptuive Technology; ICCIIDT London - UK
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| Language |
en
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| Rights |
Authors who submit to this conference agree to the following terms: a) Authors retain copyright over their work, while allowing the conference to place this unpublished work under a Creative Commons Attribution License, which allows others to freely access, use, and share the work, with an acknowledgement of the work's authorship and its initial presentation at this conference. b) Authors are able to waive the terms of the CC license and enter into separate, additional contractual arrangements for the non-exclusive distribution and subsequent publication of this work (e.g., publish a revised version in a journal, post it to an institutional repository or publish it in a book), with an acknowledgement of its initial presentation at this conference. c) In addition, authors are encouraged to post and share their work online (e.g., in institutional repositories or on their website) at any point before and after the conference. |
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