DocumentCode
2115926
Title
Towards understanding what makes 3D objects appear simple or complex
Author
Sukumar, Sreenivas R. ; Page, David L. ; Koschan, Andreas F. ; Abidi, Mongi A.
Author_Institution
Robot. & Intell. Syst. Lab., Tennessee Univ., Knoxville, TN
fYear
2008
fDate
23-28 June 2008
Firstpage
1
Lastpage
8
Abstract
Humans perceive some objects more complex than others and learning or describing a particular object is directly related to the judged complexity. Towards the goal of understanding why the geometry of some 3D objects appear more complex than others, we conducted a psychophysical study and identified contributing attributes. Our experiments conclude that surface variation, symmetry, part count, simpler part decomposability, intricate details and topology are six significant dimensions that influence 3D visual shape complexity. With that knowledge, we present a method of quantifying complexity and show that the informational aspect of Shannonpsilas theory agrees with the human notion of shape complexity.
Keywords
computational complexity; computational geometry; information theory; topology; 3D objects; 3D visual shape complexity; Shannon theory; object geometry; part decomposability; surface variation; topology; Computer aided engineering; Computer vision; Humans; Image analysis; Intelligent robots; Intelligent systems; Layout; Shape measurement; Size measurement; Surface morphology;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location
Anchorage, AK
ISSN
2160-7508
Print_ISBN
978-1-4244-2339-2
Electronic_ISBN
2160-7508
Type
conf
DOI
10.1109/CVPRW.2008.4562975
Filename
4562975
Link To Document