View-based approaches to Spatial Representation in Human Vision

Andrew Glennerster 1 Miles Hansard 2 Andrew Fitzgibbon 3
2 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : In an immersive virtual environment, observers fail to notice the expansion of a room around them and consequently make gross errors when comparing the size of objects. This result is difficult to explain if the visual system continuously generates a 3-D model of the scene based on known baseline information from interocular separation or proprioception as the observer walks. An alternative is that observers use view-based methods to guide their actions and to represent the spatial layout of the scene. In this case, they may have an expectation of the images they will receive but be insensitive to the rate at which images arrive as they walk. We describe the way in which the eye movement strategy of animals simplifies motion processing if their goal is to move towards a desired image and discuss dorsal and ventral stream processing of moving images in that context. Although many questions about view-based approaches to scene representation remain unanswered, the solutions are likely
Document type :
Conference papers
Complete list of metadatas

Cited literature [49 references]  Display  Hide  Download

https://hal.inria.fr/inria-00435556
Contributor : Miles Hansard <>
Submitted on : Tuesday, November 24, 2009 - 1:59:29 PM
Last modification on : Wednesday, April 11, 2018 - 1:58:43 AM
Long-term archiving on : Thursday, June 17, 2010 - 9:44:38 PM

File

view_based.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Andrew Glennerster, Miles Hansard, Andrew Fitzgibbon. View-based approaches to Spatial Representation in Human Vision. Dagstuhl Seminar on Statistical and Geometrical Approaches to Visual Motion Analysis, Jul 2008, Dagstuhl, Germany. pp.193-208, ⟨10.1007/978-3-642-03061-1_10⟩. ⟨inria-00435556⟩

Share

Metrics

Record views

325

Files downloads

205