Paper Info
Title
Object rigidity and reflectivity identification based on motion analysis
Abstract
Rigidity and reflectivity are important properties of objects, identifying these properties is a fundamental problem for many computer vision applications like motion and tracking. In this paper, we extend our previous work to propose a motion analysis based approach for detecting the object's rigidity and reflectivity. This approach consists of two steps. The first step aims to identify object rigidity based on motion estimation and optic flow matching. The second step is to classify specular rigid and diffuse rigid objects using structure from motion and Procrustes analysis. We show how rigid bodies can be detected without knowing any prior motion information by using a mutual information based matching method. In addition, we use a statistic way to set thresholds for rigidity classification. Presented results demonstrate that our approach can efficiently classify the rigidity and reflectivity of an object.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652288
ICIP
Keywords
Field
DocType
mutual information,motion analysis,rigidity,image matching,rigidity classification,mutual information based matching,optic flow,motion estimation,reflectivity,image classification,procrustes analysis,computer vision,reflectivity identification,optic flow matching,object rigidity,optical imaging,structure from motion,adaptive optics,shape,rigid body,optical flow,object recognition
Rigidity (psychology),Structure from motion,Computer vision,Pattern recognition,Computer science,Procrustes analysis,Artificial intelligence,Mutual information,Motion estimation,Motion analysis,Contextual image classification,Cognitive neuroscience of visual object recognition
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
Di Zang19812.40
Paul R. Schrater214122.71
Katja Doerschner352.23