Segmenting the motion components of a video: A long-term unsupervised model

arXiv:2310.01040v3 Announce Type: replace
Abstract: Human beings have the ability to continuously analyze a video and immediately extract the motion components. We want to adopt this paradigm to provide a coherent and stable motion segmentation over the video sequence. In this perspective, we propose a novel long-term spatio-temporal model operating in a totally unsupervised way. It takes as input the volume of consecutive optical flow (OF) fields, and delivers a volume of segments of coherent motion over the video. More …

abstract analyze arxiv beings components cs.cv extract human long-term novel paradigm perspective segmentation temporal type unsupervised video