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Detection of Multi-Part Objects by Top-Down Perceptual Grouping
- Source :
- CRV
- Publication Year :
- 2005
- Publisher :
- IEEE, 2005.
-
Abstract
- In this paper, a top-down approach based on perceptual grouping is proposed for multi-part objects detection. The abstract conceptual category of multi-part objects is formalized by a set of global criteria. These criteria will enable the evaluation of the segmentation quality in order to determine if the whole grouping is perceptually significant and if it has a good perceptual shape. A new cognitive vision methodology, called SAFE (subjectivity and formalism explicitly), is presented. Its goal is to help identify the proper global criteria and to validate the judgment derived from formal calculations of these criteria by human judgment.
- Subjects :
- business.industry
Computer science
media_common.quotation_subject
Cognitive neuroscience of visual object recognition
Top-down and bottom-up design
Image segmentation
Machine learning
computer.software_genre
Object detection
Perception
Segmentation
Quality (business)
Artificial intelligence
business
Set (psychology)
computer
media_common
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)
- Accession number :
- edsair.doi...........baa6ffe9777079820e473881cd68437d
- Full Text :
- https://doi.org/10.1109/crv.2005.34