Multi view registration for novelty/background separation

We propose a system for the automatic segmentation of novelties from the background in scenarios where multiple images of the same environment are available e.g. obtained by wearable visual cameras. Our method finds the pixels in a query image corresponding to the underlying background environment by comparing it to reference images of the same scene. This is achieved despite the fact that all the images may have different viewpoints , significantly different illumination conditions and contain different objects cars, people, bicycles, etc. - occluding the background. We estimate the probability of each pixel, in the query image, belonging to the background by computing its appearance inconsistency to the multiple reference images. We then, produce multiple segmentations of the query image using an iterated graph cuts algorithm, initializing from these estimated probabilities and consecutively combine these segmentations to come up with a final segmentation of the background. Detec...

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Omid Aghazadeh, Josephine Sullivan, Stefan Carlsson
• Keywords: Automatic Segmentation, Computer Vision, Cvpr 2012, Illumination Conditions, Query Image