pyTAG: python-based interactive training data generation for visual tracking algorithms (Conference Presentation)

Ekincan Ufuktepe; Vipul Ramtekkar; Ke Gao; Noor Al-Shakarji; Joshua Fraser; Hadi AliAkbarpour; Guna Seetharaman; Kannappan Palaniappan

doi:10.1117/12.2561718

27 April 2020 pyTAG: python-based interactive training data generation for visual tracking algorithms (Conference Presentation)

Ekincan Ufuktepe, Vipul Ramtekkar, Ke Gao, Noor Al-Shakarji, Joshua Fraser, Hadi AliAkbarpour, Guna Seetharaman, Kannappan Palaniappan

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Proceedings Volume 11398, Geospatial Informatics X; 113980D (2020) https://doi.org/10.1117/12.2561718
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

In this study, a rapid training data and ground truth generation tool has been implemented for visual tracking. The proposed tool's plugin structure allows integration, testing, and validation of different trackers. The tracker can be paused, resumed, forwarded, rewound and re-initialized on the run, after it loses the object, which is a needed step in the training data generation. This tool has been implemented to assist researchers to rapidly generate ground truth and training data, fix annotations, run and visualize their own single object trackers, or existing object tracking techniques.

Conference Presentation

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Ekincan Ufuktepe, Vipul Ramtekkar, Ke Gao, Noor Al-Shakarji, Joshua Fraser, Hadi AliAkbarpour, Guna Seetharaman, and Kannappan Palaniappan "pyTAG: python-based interactive training data generation for visual tracking algorithms (Conference Presentation)", Proc. SPIE 11398, Geospatial Informatics X, 113980D (27 April 2020); https://doi.org/10.1117/12.2561718

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KEYWORDS

Optical tracking

Detection and tracking algorithms

Computer vision technology

Machine learning

Machine vision

Motion models

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