Limits...
Visual perception of procedural textures: identifying perceptual dimensions and predicting generation models.

Liu J, Dong J, Cai X, Qi L, Chantler M - PLoS ONE (2015)

Bottom Line: The results suggested that existing dimensions in literature cannot accommodate random textures.We therefore utilized isometric feature mapping (Isomap) to establish a three-dimensional perceptual texture space which better explains the features used by humans in texture similarity judgment.Finally, we proposed computational models to map perceptual features to the perceptual texture space, which can suggest a procedural model to produce textures according to user-defined perceptual scales.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Technology, Ocean University of China, 238 Songling Road, Qingdao, Shandong, China; Science and Information College, Qingdao Agricultural University, 700 Changcheng Road, Qingdao, Shandong, China.

ABSTRACT
Procedural models are widely used in computer graphics for generating realistic, natural-looking textures. However, these mathematical models are not perceptually meaningful, whereas the users, such as artists and designers, would prefer to make descriptions using intuitive and perceptual characteristics like "repetitive," "directional," "structured," and so on. To make up for this gap, we investigated the perceptual dimensions of textures generated by a collection of procedural models. Two psychophysical experiments were conducted: free-grouping and rating. We applied Hierarchical Cluster Analysis (HCA) and Singular Value Decomposition (SVD) to discover the perceptual features used by the observers in grouping similar textures. The results suggested that existing dimensions in literature cannot accommodate random textures. We therefore utilized isometric feature mapping (Isomap) to establish a three-dimensional perceptual texture space which better explains the features used by humans in texture similarity judgment. Finally, we proposed computational models to map perceptual features to the perceptual texture space, which can suggest a procedural model to produce textures according to user-defined perceptual scales.

No MeSH data available.


Three dimensional representation of the Perceptual Texture Space based on Isomap.The projection into the (A) x-y plane, (B) x-z plane, (C) y-z plane were shown. Points labeled with yellow, red and blue corresponded to Cluster A, Cluster B and Cluster C resulted by HCA respectively.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4481328&req=5

pone.0130335.g008: Three dimensional representation of the Perceptual Texture Space based on Isomap.The projection into the (A) x-y plane, (B) x-z plane, (C) y-z plane were shown. Points labeled with yellow, red and blue corresponded to Cluster A, Cluster B and Cluster C resulted by HCA respectively.

Mentions: Fig 8 exhibited two-dimensional projections produced by Isomap. Selected samples were superimposed on the data points. Along certain axis, textures can be perceived similar or different according to visual perceptual features. We did not interpret the dimensions as Rao [18] did, for we believed that the dimensions were difficult to describe and further psychophysical experiments were needed to assess the underlying dimensions. As shown in Fig 7, correlation analysis suggests that subjects used a combination of perceptual features as criteria while grouping textures.


Visual perception of procedural textures: identifying perceptual dimensions and predicting generation models.

Liu J, Dong J, Cai X, Qi L, Chantler M - PLoS ONE (2015)

Three dimensional representation of the Perceptual Texture Space based on Isomap.The projection into the (A) x-y plane, (B) x-z plane, (C) y-z plane were shown. Points labeled with yellow, red and blue corresponded to Cluster A, Cluster B and Cluster C resulted by HCA respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481328&req=5

pone.0130335.g008: Three dimensional representation of the Perceptual Texture Space based on Isomap.The projection into the (A) x-y plane, (B) x-z plane, (C) y-z plane were shown. Points labeled with yellow, red and blue corresponded to Cluster A, Cluster B and Cluster C resulted by HCA respectively.
Mentions: Fig 8 exhibited two-dimensional projections produced by Isomap. Selected samples were superimposed on the data points. Along certain axis, textures can be perceived similar or different according to visual perceptual features. We did not interpret the dimensions as Rao [18] did, for we believed that the dimensions were difficult to describe and further psychophysical experiments were needed to assess the underlying dimensions. As shown in Fig 7, correlation analysis suggests that subjects used a combination of perceptual features as criteria while grouping textures.

Bottom Line: The results suggested that existing dimensions in literature cannot accommodate random textures.We therefore utilized isometric feature mapping (Isomap) to establish a three-dimensional perceptual texture space which better explains the features used by humans in texture similarity judgment.Finally, we proposed computational models to map perceptual features to the perceptual texture space, which can suggest a procedural model to produce textures according to user-defined perceptual scales.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Technology, Ocean University of China, 238 Songling Road, Qingdao, Shandong, China; Science and Information College, Qingdao Agricultural University, 700 Changcheng Road, Qingdao, Shandong, China.

ABSTRACT
Procedural models are widely used in computer graphics for generating realistic, natural-looking textures. However, these mathematical models are not perceptually meaningful, whereas the users, such as artists and designers, would prefer to make descriptions using intuitive and perceptual characteristics like "repetitive," "directional," "structured," and so on. To make up for this gap, we investigated the perceptual dimensions of textures generated by a collection of procedural models. Two psychophysical experiments were conducted: free-grouping and rating. We applied Hierarchical Cluster Analysis (HCA) and Singular Value Decomposition (SVD) to discover the perceptual features used by the observers in grouping similar textures. The results suggested that existing dimensions in literature cannot accommodate random textures. We therefore utilized isometric feature mapping (Isomap) to establish a three-dimensional perceptual texture space which better explains the features used by humans in texture similarity judgment. Finally, we proposed computational models to map perceptual features to the perceptual texture space, which can suggest a procedural model to produce textures according to user-defined perceptual scales.

No MeSH data available.