A framework for estimation of motion parameters from range image
Computer Vision, Graphics, and Image Processing
Analysis and interpretation of range images
Analysis and interpretation of range images
Rigid body motion from range image sequences
CVGIP: Image Understanding
Dynamic integration of height maps into a 3D world representation from range image sequences
International Journal of Computer Vision - Special issue on machine vision research at Osaka University
Surface correspondence and motion computation from a pair of range images
Computer Vision and Image Understanding
An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
Direct Estimation of Range Flow on Deformable Shape From a Video Rate Range Camera
IEEE Transactions on Pattern Analysis and Machine Intelligence
Range Image Segmentation: Adaptive Grouping of Edges into Regions
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
Geometric matching of 3D objects: assessing the range of successful initial configurations
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Comparing Curved-Surface Range Image Segmenters
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Segmentation of Range Data into Rigid Subsets Using Surface Patches
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
An Adaptive Contour Closure Algorithm and Its Experimental Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Static and dynamic abstract formal models for 3D sensor images
WSEAS TRANSACTIONS on SYSTEMS
Multiple 3D sensor views object models correspondence
ICS'09 Proceedings of the 13th WSEAS international conference on Systems
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Traditionally, feature extraction and correspondence determination are handled separately in motion analysis of (range) image sequences. The correspondence determination methods have typically an exponential computational complexity. In the present paper we introduce a novel framework of motion analysis that unifies feature extraction and correspondence determination in a single process. Under the basic assumption of a small relative motion between the camera and the scene, feature extraction is solved by refining the segmentation result of the previous frame. This way correspondence information becomes directly available as a by-product of the feature extraction process. Due to the coupled processing of frames we also force some degree of segmentation stability. First results on real range image sequences have demonstrated the potential of our approach.