#OPENCV EYE TRACKING FULL#

Difficulties in Object TrackingР”Вespite being a beneficial method, not every market and/or process can afford to perform object tracking due to the fact that one of the crucial hurdles in training an object tracking model is the training and tracking speed. It can be thought of as looking into the future. Visual tracking is an exciting application where the future position of an object in a video is estimated without inputting the rest of the video into the algorithm. Object tracking has lately been extensively used in surveillance, security, traffic monitoring, anomaly detection, robot vision, and visual tracking. Hence, models for SOT cannot be directly applied to MOT and leads to poor accuracy. MOT poses the main difficulty in the interaction of multiple objects, to be tracked, with each other.

The latter one, for obvious reasons, is far more complicated than the former. Similarly, multiple object tracking is when various objects are being tracked simultaneously within the same video or set of frames. As understood by the name itself, single object tracking is when only a single specific object is being tracked in a video or a set of frames. One is called Single Object Tracking (SOT), and the other one, Multiple Object Tracking (MOT). Object tracking, on an abstract level, can be done with either of the two approaches existing in it. Object tracking is the method of tracking the ballРІР‚в„ўs location across the screen in real-time by estimating its trajectory. For instance, you have a video of a baseball match, and you want to track the ballРІР‚в„ўs location constantly throughout the video. Object tracking is one such application of computer vision where an object is detected in a video, otherwise interpreted as a set of frames, and the objectРІР‚в„ўs trajectory is estimated.

How can OpenCV be used in object tracking?.

The article is divided into the following sections:

#OPENCV EYE TRACKING FULL#

We start from the basics and will move on to the full implementation of an object tracking algorithm using OpenCV.

Moving on to the problem of object tracking, the following article probs the concept in a much deeper way. Now, it is being adapted in almost every other tech domain, be it medical diagnosis, autonomous cars, or background removal from images and videos. The implementation of modern computer vision techniques has exponentially revolutionized technology.

Computer vision allows the machines to perform the functions of the human eye and mind, but instead of nerves and retinas, this has to be done with the help of cameras and algorithms.Р”Р‡or the past two decades, AI-driven computer vision has provided multiple methods to perform even a single function that a human brain can accomplish related to vision. You can say as artificial intelligence has given computers the ability to think, computer vision gives them the ability to see and interpret sight. Computer vision aims to automate the processes of machines, which can be performed by human vision. That is where the idea of computer vision arose. Object Tracking with OpenCV Updated on Oct 11, 2021Р”В®ngineers and computer scientists have long been trying to allow computers to see and interpret visual data and perform certain functions based on the data collected.

Opencv eye tracking