ROSSINI: Reconstructing 3D structure from single images: a perceptual reconstruction approach

Lead Research Organisation: University of Southampton
Department Name: Sch of Psychology

Abstract

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Publications

10 25 50
 
Description The ability of human observers to identify and organise visual information into categories is a popular metric of scene recognition and understanding in behavioral and computational research. However, categorical constructs and their labels can be somewhat arbitrary. We have developed a new algorithm for describing human-centred categorisation of scene information, outperforming previous state-of-the-art descriptions in the literature.
Exploitation Route Yes. Understanding how human observers organise complex visual information will help researchers to better describe human perception, but will also enable computational models that use this information in processing natural scenes to become more efficient and effective.
Sectors Creative Economy,Digital/Communication/Information Technologies (including Software)

 
Description Depth and scene gist 
Organisation York University Toronto
Country Canada 
Sector Academic/University 
PI Contribution A collaborative research project, I am conducting the research using the SYNS dataset that was created as a key outcome of the EPSRC grant
Collaborator Contribution Addition of expertise in stereo depth processing from Professor Laurie Wilcox
Impact None yet
Start Year 2016
 
Description BMVA workshop in London 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact Around 60 people attended the workshop, whose theme was 3D reconstruction in both humans and machines. We had 2 international speakers.
Year(s) Of Engagement Activity 2020
URL https://britishmachinevisionassociation.github.io/meetings/20-01-29-3D%20worlds%20from%202D%20images...