Object-Centric Contact Modeling for Natural Hand Grasp Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for modeling hand-object interaction, such as those based on contact maps, fail to capture the structured uncertainty inherent in hand-object interaction, leading to unrealistic and unnatural interaction models with insufficient contact or excessive penetration.
Innovation Solution
A computing system generates a digital hand grasp representation using a contact model that includes a contact map, a hand part map, and a direction map, determined through a sequential and conditional framework of CVAE models, and optimized using a piecewise SDF hand model and an optimization algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a contact map is used to model hand-object interaction, then the modeling process is simplified, but the contact representation becomes insufficient and unrealistic
Solution Approach 1:
The contact representation is segmented into three distinct maps: contact map (contact locations), hand part map (contacting hand parts), and direction map (contact directions). This segmentation allows each map to capture specific aspects of hand-object interaction, resolving the contradiction by maintaining manageable complexity while significantly improving representation accuracy and completeness.
Solution Approach 2:
The patent transitions from a single 2D contact map to a multi-dimensional representation system. The contact map provides spatial location (2D), the hand part map adds part identification dimension, and the direction map adds orientation dimension. This dimensional expansion enriches the contact representation without proportionally increasing processing complexity.
2Device complexity
If a single contact map is used, then the model is simpler, but structured uncertainty in hand-object interaction is not captured
Solution Approach 1:
The model segments uncertainty into structured components through three maps. The contact map captures spatial uncertainty, the hand part map captures identification uncertainty, and the direction map captures orientation uncertainty. This segmentation transforms unstructured uncertainty into manageable, representable dimensions, improving reliability without excessive complexity.
Solution Approach 2:
Each map focuses on a specific local aspect of contact: location (contact map), part identity (hand part map), and orientation (direction map). This local quality approach allows the model to represent structured uncertainty in each dimension appropriately, enhancing overall reliability while keeping individual components simple and interpretable.
3Device complexity
If contact modeling is insufficient, then the model is simpler, but penetration and contact accuracy deteriorate
Solution Approach 1:
The patent adds multiple dimensions to contact modeling: spatial dimension (contact map), categorical dimension (hand part map), and directional dimension (direction map). This multi-dimensional approach captures contact accuracy comprehensively, resolving the contradiction by showing that the precision gain outweighs the moderate increase in model complexity.
Solution Approach 2:
The model performs preliminary classification and localization before final contact computation. By pre-determining contact locations, hand parts, and directions through the three maps, the system prepares structured contact information that guides subsequent grasp generation, improving contact accuracy without requiring overly complex real-time computation.
Data Source
AI summary
In some embodiments, a computing system receives a representation of an object from a client device. The computing system generates a contact representation for hand-object interaction based on the representation of the object. The object-centric contact representation includes a contact map indicating contact points on the representation of the object, a hand part map indicating hand parts contacting the object, and a direction map comprising contact directions of the hand parts contacting the object. The computing system generates a hand grasp representation with respect to the object based on the contact representation using a model-based optimization algorithm. The computing system provides the hand grasp representation to the client device.