Object tracking is a concept employed within Artificial Intelligence which involves locating and following one or multiple specific objects over a video sequence or set of images. This necessitates the detection of the subject object(s) in each frame, calculating its position and motion, then utilizing that data to forecast their location in upcoming frames.
Object tracking is essential for tasks such as surveillance, robotics, driverless cars and augmented reality, thus making it a focal point for research in computer vision and artificial intelligence. A range of techniques are available for this purpose such as feature-based strategies, correlation filters, optical flow and deep learning-aligned approaches.
The complexity of object tracking increases when the subject items are quickly moving, undergo an alteration in appearance, or become concealed by other objects on the scene. As such, developing efficient object tracking algorithms is being vigorously pursued in computer vision and AI.
Applications Of Object Tracking AcrossVarious Fields:
- Object tracking is used in security systems to detect and monitor potential threats. It is deployed in public places such as airports, railway stations, and shopping malls.
- Robotics employ object tracking for navigation, object grasping and manipulation, and autonomous vehicles.
- In sports, it is used to track the position and movement of athletes during training and competitions in order to analyze their performance and provide feedback.
- Augmented reality applications use object tracking to overlay digital information onto real-world objects for gaming, advertising and education purposes.
- Automotive applications such as self-driving cars make use of object tracking to monitor the position and movement of other vehicles, pedestrians, and obstacles on the road.
- Finally, it is widely used in medical imaging to track the position and movement of organs, tissues, and tumors for cancer treatment, radiation therapy, and surgery planning.
