A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast ISODATA clustering algorithms
Pattern Recognition
COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast, minimum storage ray-triangle intersection
Journal of Graphics Tools
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Point Signatures: A New Representation for 3D Object Recognition
International Journal of Computer Vision
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
A New Paradigm for Recognizing 3-D Object Shapes from Range Data
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
3D Free-Form Object Recognition in Range Images Using Local Surface Patches
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D free-form object recognition in range images using local surface patches
Pattern Recognition Letters
Large data sets and confusing scenes in 3-D surface matching and recognition
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Parts-based 3D object classification
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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Viewpoint independent recognition of free-form objects and estimation of their exact position are a complex procedure with applications in robotics, artificial intelligence, computer vision and many other scientific fields. In this paper a novel approach is presented that addresses recognition of objects lying in highly cluttered and occluded scenes. The proposed procedure relies on distance maps, which are extracted and stored off-line for each of the 3D objects that might be contained in the scene. During the on-line recognition procedure distance maps are extracted from the scene. Greyscale images, derived from scene's distance maps, are matched with those of the object under recognition by applying similarity measures to the descriptors that are extracted from the images. The similarity is then estimated from image patches, which are defined using the SIFT descriptor in an appropriate way. After finding the best similarities the position of the object in the scene is estimated. This process is repeated until all objects are successfully recognized. Multiple experiments, which were performed on both 2.5D synthetic and real scenes, proved that the proposed method is robust and highly efficient to a satisfactory degree of occlusion and clutter.