ACM Transactions on Graphics (TOG)
3D zernike descriptors for content based shape retrieval
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Surface registration by matching oriented points
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Handrix: animating the human hand
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Synthesizing animations of human manipulation tasks
ACM SIGGRAPH 2004 Papers
Fully Automatic Registration of 3D Point Clouds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A review of recent range image registration methods with accuracy evaluation
Image and Vision Computing
Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning
IEEE Transactions on Visualization and Computer Graphics
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Robotic Grasping of Novel Objects using Vision
International Journal of Robotics Research
Learning grasp strategies with partial shape information
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Sampling strategies for bag-of-features image classification
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Manipulation of unmodeled objects using intelligent grasping schemes
IEEE Transactions on Fuzzy Systems
Autonomous Robots
Scene parsing using a prior world model
International Journal of Robotics Research
Stable grasping under pose uncertainty using tactile feedback
Autonomous Robots
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To grasp a novel object, we can index it into a database of known 3D models and use precomputed grasp data for those models to suggest a new grasp. We refer to this idea as data-driven grasping, and we have previously introduced the Columbia Grasp Database for this purpose. In this paper we demonstrate a data-driven grasp planner that requires only partial 3D data of an object in order to grasp it. To achieve this, we introduce a new shape descriptor for partial 3D range data, along with an alignment method that can rigidly register partial 3D models to models that are globally similar but not identical. Our method uses SIFT features of depth images, and encapsulates "nearby" views of an object in a compact shape descriptor.