Categorizing Video Datasets: Video Object Detection, Multiple and Single Object Tracking

Categorizing Video Datasets: Video Object Detection, Multiple and Single Object Tracking
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© 2024 by IJETT Journal
Volume-72 Issue-3
Year of Publication : 2024
Author : Sara Bouraya, Abdessamad Belangour
DOI : 10.14445/22315381/IJETT-V72I3P110

How to Cite?

Sara Bouraya, Abdessamad Belangour, "Categorizing Video Datasets: Video Object Detection, Multiple and Single Object Tracking," International Journal of Engineering Trends and Technology, vol. 72, no. 3, pp. 99-105, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I3P110

Abstract
Video Object detection, Single Object detection, Multiple Object Detection are crucial tasks in computer vision, enabling various real-world applications. The success of these tasks algorithms heavily relies on the availability of high-quality datasets for training and evaluation. This paper presents a comprehensive categorization of datasets specifically designed for multiple object detection, single object detection, and video object detection tasks in computer vision. Object detection and tracking are fundamental problems in the field, and accurate and diverse datasets are essential for training and evaluating detection and tracking algorithms effectively. By analyzing the characteristics of datasets for multiple object detection, single object detection, and video object detection, this paper serves as a valuable resource to drive advancements in object detection, tracking algorithms and systems. Accurate and diverse datasets are pivotal in the pursuit of robust and efficient object detection, tracking solutions across various applications in computer vision.

Keywords
Multiple Object Tracking, Single Object Tracking, Video Object Detection, Video Dataset, VOD dataset, MOT dataset, SOT dataset.

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