Track-Me-Down Emergency Location Service Provider
Object tracking and detection are fundamental and challenging tasks in various computer vision applications, spanning surveillance, vehicle navigation, and autonomous robot control. These tasks are particularly critical in the context of video monitoring within dynamic environments, where the detect...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-02-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/59/1/235 |
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| Summary: | Object tracking and detection are fundamental and challenging tasks in various computer vision applications, spanning surveillance, vehicle navigation, and autonomous robot control. These tasks are particularly critical in the context of video monitoring within dynamic environments, where the detection and tracking of objects, such as people and automobiles, play a pivotal role. In today’s world, as we combat crime and terrorism, ensure public safety, and manage traffic effectively, advanced computer vision technology has become indispensable. Video monitoring in dynamic environments is at the forefront of this battle, providing crucial insights and real-time information for decision making. Object-tracking-based techniques emerge as a strong choice, especially for detecting stationary foreground objects. These methods exhibit robust performances when the camera remains stationary, even in scenarios in which the ambient lighting conditions gradually change. This stability makes them well suited for applications requiring consistent and reliable object detection. In the contemporary landscape, one of the most pressing concerns revolves around the recognition of objects and the real-time tracking of their locations. Achieving these objectives is paramount for enhancing security, safety, and efficiency across various domains. However, it is essential to acknowledge that, in some scenarios, such as remote or isolated locations with limited Internet connectivity, access to advanced object-tracking and detection technologies may be constrained. Therefore, addressing these challenges and developing robust, offline-capable solutions remains a critical area of research and development in computer vision. In conclusion, object tracking and detection are pivotal technologies in computer vision, with applications spanning from surveillance to traffic management. In dynamic environments, they play a crucial role in enhancing security and safety. However, addressing the challenges related to real-time tracking and detection in resource-constrained settings is an ongoing research endeavor. |
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| ISSN: | 2673-4591 |