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Sökning: id:"swepub:oai:DiVA.org:kth-105314" > Multi view registra...

Multi view registration for novelty/background separation

Aghazadeh, Omid (författare)
KTH,Datorseende och robotik, CVAP
Sullivan, Josephine (författare)
KTH,Datorseende och robotik, CVAP
Carlsson, Stefan (författare)
KTH,Datorseende och robotik, CVAP
 (creator_code:org_t)
IEEE Computer Society, 2012
2012
Engelska.
Ingår i: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. - : IEEE Computer Society. - 9781467312264 ; , s. 757-764
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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. Detection of the background in turn highlights the novel pixels. We demonstrate the effectiveness of our approach on a challenging outdoors data set.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

Automatic segmentations
Background environment
Data sets
Graph cut
Illumination conditions
Multi-view registration
Multiple image
Multiple reference images
Multiple segmentation
Query images
Reference image
Computer vision
Pixels
Image segmentation

Publikations- och innehållstyp

ref (ämneskategori)
kon (ämneskategori)

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