Group-Based Haptic Data Signaling for Body-Part Targeting
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Solution Overview
Problem
Existing haptic technologies face challenges in efficiently adapting haptic effects to specific parts of the human body due to the use of simplified body models like skeletons or meshes, which either limit adaptation or require excessive data transmission.
Innovation Solution
A method and apparatus for signaling and parsing haptic data using a body model with a first plurality of body parts and a second plurality of groups, where data is encoded and decoded to identify targeted body parts by referencing groups, reducing data volume and optimizing processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a simplified body model like a skeleton is used, then device complexity is reduced, but haptic effect adaptation precision deteriorates
Solution Approach 1:
The body model is segmented into a hierarchical structure with multiple levels: a simplified skeleton framework (joints and segments) combined with detailed body part information. This segmentation allows the system to maintain low overall complexity while achieving high precision at the body part level where it matters most for haptic rendering.
Solution Approach 2:
The patent adds a hierarchical dimension to the body model representation by organizing body parts into groups and subgroups. This dimensional organization allows efficient data structure where common properties can be defined at higher levels and inherited by specific body parts, reducing redundancy while maintaining precision.
2Manufacturing precision
If a mesh body model is used, then haptic effect adaptation precision is improved, but data transmission volume increases
Solution Approach 1:
The patent extracts only the essential geometric and identification information needed for haptic rendering from complete mesh models. By taking out only the critical body part identification data and essential geometric properties, the system achieves accurate haptic adaptation without transmitting the full mesh data, significantly reducing data volume.
Solution Approach 2:
Instead of transmitting complete mesh models, the patent uses simplified representations (copies) of body parts that contain only the necessary identification and geometric information for haptic rendering. These copies are sufficient for the intended purpose while being much more compact than full mesh data.
3Manufacturing precision
If detailed body part identification is implemented, then haptic effect rendering precision is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary organization of body part data into hierarchical groups and establishes identification mappings in advance. This preliminary action allows the system to quickly retrieve and process only the relevant body part information during haptic rendering, avoiding the need to process all body parts or search through unorganized data structures.
Solution Approach 2:
The patent applies detailed identification and processing only to the specific body parts that are actually targeted by haptic effects, rather than uniformly processing all body parts. This local quality approach ensures high precision where needed while minimizing processing overhead for non-targeted areas.
Data Source
AI summary
Methods and apparatus of signaling/parsing data representative of a mapping between a haptic effect and one or more body parts of a body model targeted by the haptic effect are disclosed. The body model includes a first plurality of body parts, e.g., fingers, hands, phalanxes, head, and a second plurality of groups of body parts. Each group of the second plurality comprises one or more body part(s) of the first plurality. The signaling/parsing of the data comprises writing/reading, into/from a container, first data identifying the targeted body part with reference to one or more groups of the second plurality the targeted body part belongs to.