#315:
N. Al-Shakarji,
E. Ufuktepe,
F. Bunyak,
H. Aliakbarpour,
G. Seetharaman, and
K. Palaniappan
IEEE Applied Imagery Pattern Recognition Workshop (AIPR),
pgs. 1-6,
2020
Abstract,
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With the recent advances in video sensor technologies, emergence of new applications associated with these technologies, and demand for automated video analytics have increased the need for ground-truth annotations. Researchers attempt to explore different methodologies and algorithms on different challenging datasets. Ground-truth annotations are needed for quantitative evaluation and comparison of video analysis methods, and training machine learning approaches. Ground Truth Generator (GTG) is our semi-automatic solution for rapid moving object annotation. GTG allows annotation of high densities of moving objects in a video with considerably fewer human interactions, and greatly reduces annotation effort and time. For each individual moving object in a video GTG generates bounding boxes, object classes, and motion trajectories. GTG integrates a fully-automated detection, tracking, and fusion pipeline with an interactive visualization, annotation, and editing interface. Our proposed system was tested on FPSS [1] and VisDrone [2] datasets and showed promising results.
@inproceedings{Noor2020:AIPR_Video_annotation,
author = "N. Al-Shakarji and E. Ufuktepe and F. Bunyak and H. Aliakbarpour and G. Seetharaman and K. Palaniappan",
title = "Semi-automatic system for rapid annotation of moving objects in surveillance videos using deep detection and multi-object tracking techniques",
year = 2020,
booktitle = "IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
pages = "1-6",
keywords = "ground truth generator, object annotation, deep learning, object detection, tracking",
doi = "10.1109/AIPR50011.2020.9425339",
url = "https://ieeexplore.ieee.org/abstract/document/9425339"
}
N. Al-Shakarji, E. Ufuktepe, F. Bunyak, H. Aliakbarpour, G. Seetharaman, and K. Palaniappan. Semi-automatic system for rapid annotation of moving objects in surveillance videos using deep detection and multi-object tracking techniques. IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pages 1-6, 2020.
