Modeling Cue Integration in Cluttered Environments

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Standard

Modeling Cue Integration in Cluttered Environments. / Sahani, Maneesh; Whiteley, Louise.

Sensory Cue Integration. Oxford University Press, 2012.

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Harvard

Sahani, M & Whiteley, L 2012, Modeling Cue Integration in Cluttered Environments. in Sensory Cue Integration. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195387247.003.0005

APA

Sahani, M., & Whiteley, L. (2012). Modeling Cue Integration in Cluttered Environments. In Sensory Cue Integration Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195387247.003.0005

Vancouver

Sahani M, Whiteley L. Modeling Cue Integration in Cluttered Environments. In Sensory Cue Integration. Oxford University Press. 2012 https://doi.org/10.1093/acprof:oso/9780195387247.003.0005

Author

Sahani, Maneesh ; Whiteley, Louise. / Modeling Cue Integration in Cluttered Environments. Sensory Cue Integration. Oxford University Press, 2012.

Bibtex

@inbook{b8dd89f4667943198201a3b517113b2b,
title = "Modeling Cue Integration in Cluttered Environments",
abstract = "This chapter lays out one approach to describing the inferential problem encountered when integrating multiple different cues that may arise from many different objects. By switching representations from a set of discrete single-valued cues to a spatial representation based on attribute and cue {"}maps,{"} it was possible naturally to model observers' behavior in some simple multiobject and multicue settings, and provide a natural, tractable approach to approximation within these settings. But while effective in these simple cases, the framework is still far from providing a complete description of perceptual inference and integration in cluttered scenes. The framework developed here works best when the cues used for inference are inherently localized in space (in the visual case) or with respect to some other dimension important for determining grouping.",
keywords = "Attribute maps, Cue integration, Cue maps, Modeling, Perceptual inference, Single-valued cues, Spatial representation",
author = "Maneesh Sahani and Louise Whiteley",
year = "2012",
month = sep,
day = "20",
doi = "10.1093/acprof:oso/9780195387247.003.0005",
language = "English",
isbn = "9780195387247",
booktitle = "Sensory Cue Integration",
publisher = "Oxford University Press",

}

RIS

TY - CHAP

T1 - Modeling Cue Integration in Cluttered Environments

AU - Sahani, Maneesh

AU - Whiteley, Louise

PY - 2012/9/20

Y1 - 2012/9/20

N2 - This chapter lays out one approach to describing the inferential problem encountered when integrating multiple different cues that may arise from many different objects. By switching representations from a set of discrete single-valued cues to a spatial representation based on attribute and cue "maps," it was possible naturally to model observers' behavior in some simple multiobject and multicue settings, and provide a natural, tractable approach to approximation within these settings. But while effective in these simple cases, the framework is still far from providing a complete description of perceptual inference and integration in cluttered scenes. The framework developed here works best when the cues used for inference are inherently localized in space (in the visual case) or with respect to some other dimension important for determining grouping.

AB - This chapter lays out one approach to describing the inferential problem encountered when integrating multiple different cues that may arise from many different objects. By switching representations from a set of discrete single-valued cues to a spatial representation based on attribute and cue "maps," it was possible naturally to model observers' behavior in some simple multiobject and multicue settings, and provide a natural, tractable approach to approximation within these settings. But while effective in these simple cases, the framework is still far from providing a complete description of perceptual inference and integration in cluttered scenes. The framework developed here works best when the cues used for inference are inherently localized in space (in the visual case) or with respect to some other dimension important for determining grouping.

KW - Attribute maps

KW - Cue integration

KW - Cue maps

KW - Modeling

KW - Perceptual inference

KW - Single-valued cues

KW - Spatial representation

UR - http://www.scopus.com/inward/record.url?scp=84921259714&partnerID=8YFLogxK

U2 - 10.1093/acprof:oso/9780195387247.003.0005

DO - 10.1093/acprof:oso/9780195387247.003.0005

M3 - Book chapter

AN - SCOPUS:84921259714

SN - 9780195387247

BT - Sensory Cue Integration

PB - Oxford University Press

ER -

ID: 244493423