Comparing Various Tracking Algorithms In OpenCV
Main Article Content
Abstract
Locating an item in consecutive frames of a video is known as object tracking. It is implemented by estimating the state of the concerned object present in the scene from previous information. Since the object has been tracked till the present frame, it's known how it has been moving. More simply, the parameters of the model are known. A motion model tells the speed and direction of motion of the object from previous frames. Algorithms that track objects using this motion model are known as object tracking algorithms. There is a multitude of algorithms that can be used for the same purpose. The trouble is finding out which object tracking algorithms are best for a particular use case. In this work, we have compared two object tracking algorithms and their hybrid to find which performs better in the case of a live feed.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
