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This research investigates the principles of human vision through the lens of Gestalt laws, focusing on how generic segments and curve partition points (CPPs) are categorized and detected. It outlines eight categories of generic segments and curve partition points, alongside experimental results demonstrating how visual elements like parallelograms and ellipses are classified based on their edge segments. Key findings include perceptual junction detection and the relationship between low-level and high-level perceptual junctions. This work contributes to understanding image processing and vision science.
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Perceptify Vocabularies Xiaofen Zheng Faculty of Computer Science Dalhousie University
Human Vision • Gestalt Laws
GET Models Curve Partition Points Generic Segments The eight categories of generic segments. The eight categories of curve partition points. GS Description CPP Description
Edge trace and CPPs illustration The original image Experimental Results
Experimental Results (Cont’d) The original image Edge trace and CPPs illustration
Classification Experimental Result The original image The eight categories of generic segments.
Perceptual Junctions Low-level PJs High-level PJs LPJs descriptions HPJs descriptions
Perceptual junction detection and classification results HPJY : HPJA: HPJT : HPJC: LPJ: Experimental Result The original image
Parallelogram The definition of parallelogram Grouping Ellipse Grouping Parallelogram Grouping A parallelogram model An ellipse model Ellipse The definition of ellipse
Experimental Results The edge segments and CPPs Ellipses grouping (confidence >= 75%) The original image Confidence
Experimental Results (Cont’d) Parallelograms grouping (confidence >= 75%) The edge segments and CPPs The original image