Fragmented Occlusion in Computer Vision (OFAI Lecture by Roman Pflugfelder)
Channel: Austrian Research Institute for AI (OFAI)
Date: 23/09/2022

Fragmented Occlusion in Computer Vision
Dipl.-Ing. Dr. techn. Roman Pflugfelder, TU München / Technion
21 September 2022

Occlusion is an important and persistent problem in computer vision. Most of the modern, visual recognition algorithms suffer from occlusion. Making algorithms robust to occlusion is challenging, as occlusion is the result of an information loss that emerges from the projection of a three dimensional world onto a two dimensional image. This lecture will introduce fragmented or dynamic occlusion which appears when looking through foliage or when looking through a fence while walking. The problem is known in cognitive science but mostly ignored in computer vision. The current results in cognitive science tell us the importance of the temporal dimension in vision which introduces important clues for visual recognition under fragmented occlusion. Concepts such as the spatiotemporal form integration rely on motion percepts. Inspired by these psychological results, I will introduce a new video processing approach which is named video deocclusion. This approach is able to deocclude a fragmentally occluded, unknown object of interest in a sequence of images. I will also present results of a new algorithm based on deep learning which is able to localise persons behind trees where state-of-the-art object detection algorithms fail. This research is fruitful for a better understanding of the astonishing capabilities of human vision under dynamic occlusion. It is also useful for future applications of computer vision in natural environments.