Essays about: "Depth Tracking"
Showing result 6 - 10 of 75 essays containing the words Depth Tracking.
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6. Graph Neural Networks for Events Detection in Football
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Tracab’s optical tracking system allows to track the 2-dimensional trajectories of players and ball during a football game. Using this data it is possible to train machine learning models to identify events that happen during the match. READ MORE
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7. Detecting Successful Throws
University essay from Örebro universitet/Institutionen för naturvetenskap och teknikAbstract : This project aims to create a robot system that can accurately figure out if the throws are successful. This can help make various industrial tasks more efficient. The system uses implemented methods to process data from fisheye camera data and depth sensor data, to check the quality of the throws. READ MORE
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8. Monocular 3D Human Pose Estimation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The focus of this work is the task of 3D human pose estimation, more specifically by making use of key points located in single monocular images in order to estimate the location of human body joints in a 3D space. It was done in association with Tracab, a company based in Stockholm, who specialises in advanced sports tracking and analytics solutions. READ MORE
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9. The development of a Hardware-in-the-Loop test setup for event-based vision near-space space objects.
University essay from Luleå tekniska universitet/RymdteknikAbstract : The purpose of this thesis work was to develop a Hardware-in-the-Loop imaging setup that enables experimenting with an event-based and frame-based camera under simulated space conditions. The generated data sets were used to compare visual navigation algorithms in terms of an event-based and frame-based feature detection and tracking algorithm. READ MORE
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10. Image and RADAR fusion for autonomous vehicles
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Robust detection, localization, and tracking of objects are essential for autonomous driving. Computer vision has largely driven development based on camera sensors in recent years, but 3D localization from images is still challenging. Sensors such as LiDAR or RADAR are used to compute depth; each having its own advantages and drawbacks. READ MORE