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Event-based occlusion removal
Unwanted camera occlusions, such as debris, dust, raindrops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. This project aims to leverage the unique capabilities of event-based vision sensors to address the challenge of dynamic occlusions. By improving the reliability and accuracy of vision systems, this work could benefit a wide range of applications, from autonomous driving and drone navigation to environmental monitoring and augmented reality.
Unwanted camera occlusions, such as debris, dust, raindrops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. This project aims to leverage the unique capabilities of event-based vision sensors to address the challenge of dynamic occlusions. By improving the reliability and accuracy of vision systems, this work could benefit a wide range of applications, from autonomous driving and drone navigation to environmental monitoring and augmented reality.
Unwanted camera occlusions, such as debris, dust, raindrops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. This project aims to leverage the unique capabilities of event-based vision sensors to address the challenge of dynamic occlusions. By improving the reliability and accuracy of vision systems, this work could benefit a wide range of applications, from autonomous driving and drone navigation to environmental monitoring and augmented reality.
The goal of this project is to develop an advanced computational framework capable of identifying and eliminating dynamic occlusions from visual data in real-time, utilizing the high temporal resolution of event-based vision sensors.
The goal of this project is to develop an advanced computational framework capable of identifying and eliminating dynamic occlusions from visual data in real-time, utilizing the high temporal resolution of event-based vision sensors.