A research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology has come up with a new technology that enhances the ability of robots to visually track moving objects. Object tracking and detection, to improve the ability of optical robots to track objects.
In detail, the university published a summary of the new research, in which it explained that the robots depend in their ability to distinguish images on algorithms capable of recognizing images through cameras and sensors, as the software creates a map of the environment and distinguishes patterns, which contributes to the robot’s understanding of the surrounding environment, where the programming is Robots on the human hand to be able to see the objects identified by him.
She indicated that the research team included Assistant Professor Dr. Sajid Javed, Professor Dr. George Dias, Professor Dr. Lakmal Seneviratni, and Dr. Nofal Warghi, in cooperation with Dr. Arif Mahmoud from University of Science and Technology in Pakistan.
Dr. Sajid Javed said: “Visual tracking of objects is difficult in many robotic applications, and the difficulty lies in the process of developing monitoring algorithms that are able to act in the event of blurring of images, due to their movement, ignoring the body’s surroundings and dealing with optical variables.”
He pointed out that optical tracking of objects is a deep learning application, through which the program detects an initial set of objects and tracks their movement, as the algorithms allow the robot to automatically identify and interpret objects in the form of a set of paths and predict the end of their path.
He explained that the first step for tracking objects is to detect them, as the research team’s system contributes to teaching the robot to search for one or more pre-determined objects, and when identifying the object, it must be tracked.
He added, “The object-tracking algorithms must be characterized by high accuracy in detecting objects and locating them in the least amount of time.”
Outstanding results
The research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology tested the algorithm that it developed on six standard databases, and compared it with 33 advanced trackers currently available. The test results achieved a remarkable distinction, representing high accuracy and effectiveness in many tests.
A research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology has come up with a new technology that enhances the ability of robots to visually track moving objects. Object tracking and detection, to improve the ability of optical robots to track objects.
In detail, the university published a summary of the new research, in which it explained that the robots depend in their ability to distinguish images on algorithms capable of recognizing images through cameras and sensors, as the software creates a map of the environment and distinguishes patterns, which contributes to the robot’s understanding of the surrounding environment, where the programming is Robots on the human hand to be able to see the objects identified by him.
She indicated that the research team included Assistant Professor Dr. Sajid Javed, Professor Dr. George Dias, Professor Dr. Lakmal Seneviratni, and Dr. Nofal Warghi, in cooperation with Dr. Arif Mahmoud from University of Science and Technology in Pakistan.
Dr. Sajid Javed said: “Visual tracking of objects is difficult in many robotic applications, and the difficulty lies in the process of developing monitoring algorithms that are able to act in the event of blurring of images, due to their movement, ignoring the body’s surroundings and dealing with optical variables.”
He pointed out that optical tracking of objects is a deep learning application, through which the program detects an initial set of objects and tracks their movement, as the algorithms allow the robot to automatically identify and interpret objects in the form of a set of paths and predict the end of their path.
He explained that the first step for tracking objects is to detect them, as the research team’s system contributes to teaching the robot to search for one or more pre-determined objects, and when identifying the object, it must be tracked.
He added, “The object-tracking algorithms must be characterized by high accuracy in detecting objects and locating them in the least amount of time.”
Outstanding results
The research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology tested the algorithm that it developed on six standard databases, and compared it with 33 advanced trackers currently available. The test results achieved a remarkable distinction, representing high accuracy and effectiveness in many tests.
A research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology has come up with a new technology that enhances the ability of robots to visually track moving objects. Object tracking and detection, to improve the ability of optical robots to track objects.
In detail, the university published a summary of the new research, in which it explained that the robots depend in their ability to distinguish images on algorithms capable of recognizing images through cameras and sensors, as the software creates a map of the environment and distinguishes patterns, which contributes to the robot’s understanding of the surrounding environment, where the programming is Robots on the human hand to be able to see the objects identified by him.
She indicated that the research team included Assistant Professor Dr. Sajid Javed, Professor Dr. George Dias, Professor Dr. Lakmal Seneviratni, and Dr. Nofal Warghi, in cooperation with Dr. Arif Mahmoud from University of Science and Technology in Pakistan.
Dr. Sajid Javed said: “Visual tracking of objects is difficult in many robotic applications, and the difficulty lies in the process of developing monitoring algorithms that are able to act in the event of blurring of images, due to their movement, ignoring the body’s surroundings and dealing with optical variables.”
He pointed out that optical tracking of objects is a deep learning application, through which the program detects an initial set of objects and tracks their movement, as the algorithms allow the robot to automatically identify and interpret objects in the form of a set of paths and predict the end of their path.
He explained that the first step for tracking objects is to detect them, as the research team’s system contributes to teaching the robot to search for one or more pre-determined objects, and when identifying the object, it must be tracked.
He added, “The object-tracking algorithms must be characterized by high accuracy in detecting objects and locating them in the least amount of time.”
Outstanding results
The research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology tested the algorithm that it developed on six standard databases, and compared it with 33 advanced trackers currently available. The test results achieved a remarkable distinction, representing high accuracy and effectiveness in many tests.
A research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology has come up with a new technology that enhances the ability of robots to visually track moving objects. Object tracking and detection, to improve the ability of optical robots to track objects.
In detail, the university published a summary of the new research, in which it explained that the robots depend in their ability to distinguish images on algorithms capable of recognizing images through cameras and sensors, as the software creates a map of the environment and distinguishes patterns, which contributes to the robot’s understanding of the surrounding environment, where the programming is Robots on the human hand to be able to see the objects identified by him.
She indicated that the research team included Assistant Professor Dr. Sajid Javed, Professor Dr. George Dias, Professor Dr. Lakmal Seneviratni, and Dr. Nofal Warghi, in cooperation with Dr. Arif Mahmoud from University of Science and Technology in Pakistan.
Dr. Sajid Javed said: “Visual tracking of objects is difficult in many robotic applications, and the difficulty lies in the process of developing monitoring algorithms that are able to act in the event of blurring of images, due to their movement, ignoring the body’s surroundings and dealing with optical variables.”
He pointed out that optical tracking of objects is a deep learning application, through which the program detects an initial set of objects and tracks their movement, as the algorithms allow the robot to automatically identify and interpret objects in the form of a set of paths and predict the end of their path.
He explained that the first step for tracking objects is to detect them, as the research team’s system contributes to teaching the robot to search for one or more pre-determined objects, and when identifying the object, it must be tracked.
He added, “The object-tracking algorithms must be characterized by high accuracy in detecting objects and locating them in the least amount of time.”
Outstanding results
The research team from the Department of Electrical Engineering and Computer Science at Khalifa University of Science and Technology tested the algorithm that it developed on six standard databases, and compared it with 33 advanced trackers currently available. The test results achieved a remarkable distinction, representing high accuracy and effectiveness in many tests.