Adapting Virtual Skeletons via Device Capability Profiles
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Solution Overview
Problem
Conventional techniques for designing virtual skeletons for avatars are time-consuming and resource-intensive, leading to unnecessary processor overhead, memory usage, and battery drain in computing devices, especially when rendering complex avatars on diverse hardware platforms.
Innovation Solution
Adapting virtual skeletons based on capability profiles, which analyze hardware capabilities to reduce complexity by eliminating unnecessary joints or segments, resulting in a less complex virtual skeleton that aligns with the computing device's resources, thereby reducing processor and graphic loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a complex master virtual skeleton is used for all computing devices, then rendering accuracy and avatar movement quality are improved, but processor overhead, memory usage, and battery drain increase
Solution Approach 1:
The virtual skeleton is segmented into multiple versions with different levels of complexity. Each computing device receives an appropriately complex version based on its capabilities, rather than all devices receiving the same complex master skeleton. This segmentation allows rendering accuracy to be maintained on capable devices while reducing energy consumption on less powerful devices.
Solution Approach 2:
Different computing devices receive different quality levels of virtual skeleton data based on their local capabilities. Devices with higher processing power receive more detailed skeletons, while devices with limited resources receive simplified versions. This local quality adaptation ensures each device operates at its optimal performance point.
2Manufacturing precision
If a complex master virtual skeleton is used for all computing devices, then avatar movement quality is improved, but device complexity and resource requirements increase
Solution Approach 1:
The system dynamically adapts the virtual skeleton complexity to match each computing device's capabilities. Rather than using a static complex skeleton for all devices, the system adjusts the skeleton's detail level based on device performance characteristics, making the complexity dynamic rather than fixed.
Solution Approach 2:
The complexity parameters of the virtual skeleton (such as number of joints, segments, and animation channels) are changed based on device capabilities. By adjusting these parameters, the system maintains avatar movement quality where possible while reducing complexity where resources are limited.
3Adaptability or versatility
If conventional techniques are used to design virtual skeletons for each computing device, then device-specific optimization is achieved, but design time and processor overhead increase
Solution Approach 1:
The system performs preliminary action by pre-defining multiple virtual skeleton versions with different complexity levels before deployment. This eliminates the need for time-consuming per-device design processes, as devices can directly use the pre-prepared appropriate version based on their capabilities.
Solution Approach 2:
Instead of redesigning virtual skeletons for each device, the system changes parameters (complexity level, detail resolution) of pre-existing skeleton templates to match device capabilities. This parameter-based adaptation is much faster than conventional design techniques.
Data Source
AI summary
A virtual skeleton may be adapted based on a capability profile. The virtual skeleton adapted based on a capability profile may be generated from a master virtual skeleton. The adapted virtual skeleton may be less complex than the master virtual skeleton. The adapted virtual skeleton may include fewer virtual skeletal joints than a number of virtual skeletal joints associated with the master virtual skeleton.