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Full-Text Articles in Engineering
Learning To Detect Pedestrian Flow In Traffic Intersections From Synthetic Data, Abhijit Baul
Learning To Detect Pedestrian Flow In Traffic Intersections From Synthetic Data, Abhijit Baul
Theses and Dissertations
Detecting pedestrian flow in different directions at at traffic-intersection has always been a challenging task. Challenges include different weather conditions, different crowd densities, occlusions, lack of available data, and so on. The emergence of deep learning and computer vision algorithms has shown promises to deal with these problems. Most of the recent works only focus on either detecting combined pedestrian flow or counting the total number of pedestrians. In this work, we have tried to detect not only combined pedestrian flow but also pedestrian flow indifferent directions. Our contributions are, 1) we are introducing a synthetic pedestrian dataset that we …
Using Motion Capture And Augmented Reality To Test Aar With Boom Occlusion, Vincent J. Bownes
Using Motion Capture And Augmented Reality To Test Aar With Boom Occlusion, Vincent J. Bownes
Theses and Dissertations
The operational capability of drones is limited by their inability to perform aerial refueling. This can be overcome by automating the process with a computer vision solution. Previous work has demonstrated the feasibility of automated aerial refueling (AAR) in simulation. To progress this technique to the real world, this thesis conducts experiments using real images of a physical aircraft replica and a motion capture system for truth data. It also compares the error between the real and virtual experiments to validate the fidelity of the simulation. Results indicate that the current technique is effective on real images and that the …
Methods For Object Tracking With Machine Vision, Zachary Simon Stamler
Methods For Object Tracking With Machine Vision, Zachary Simon Stamler
Dissertations and Theses
As machine learning and deep learning systems continue to find applications in science and engineering, the problem of providing these systems with high-quality data continues to increase in importance. Many of these systems utilize machine vision as their primary source of information, and in order to maximally leverage their abilities it is important to be able to provide them with high quality, accurate data. Unfortunately, many sets of tracking data extracted from video suffer from the problem of missing frames, which can arise from a multitude of causes depending on the system. These missing frames can result in confusion between …