Gesture Recognition System Isolating Extraneous Motions
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Solution Overview
Problem
Existing computing applications face challenges in user interaction due to complex control systems that often require learning and do not accurately map real-world motions to in-game or application actions, leading to a barrier between users and the gaming or multimedia experience.
Innovation Solution
A gesture recognition system that captures and interprets motion data in a physical space, allowing users to control applications or games through natural gestures, with the ability to isolate and exclude extraneous motions, thereby enhancing user interaction by providing a more intuitive interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional controls are used to manipulate game characters or application aspects, then the system provides structured control mechanisms, but the controls become difficult to learn and create a barrier between user and application
Solution Approach 1:
The patent replaces traditional mechanical control interfaces (keyboards, mice, controllers) with a gesture recognition system that captures natural human motions using imaging devices and processes them through gesture filters. This substitution eliminates the need to learn complex control schemes while maintaining systematic control capabilities.
Solution Approach 2:
The system creates a virtual representation (avatar) that copies and mirrors the user's physical gestures in real-time. This allows natural motion capture without requiring the user to learn application-specific control mappings, as the avatar automatically performs actions corresponding to the user's movements.
2Adaptability or versatility
If traditional controls are mapped to game actions, then the system provides structured control mapping, but the controls do not correspond to actual game actions or application actions
Solution Approach 1:
The patent segments the gesture recognition process into distinct components: motion capture, gesture filtering, and action mapping. This segmentation allows each component to be optimized independently, enabling accurate mapping of specific body part motions to corresponding application actions while filtering out extraneous movements.
Solution Approach 2:
The system applies different gesture filters to different body parts (hands, arms, legs, torso) based on their specific motion characteristics and relevance to application actions. This localized approach ensures that each body part's motion is interpreted according to its natural movement patterns, improving mapping accuracy.
3Measurement precision
If the system captures all motion data from the user, then the system captures complete user behavior, but random and extraneous motions interfere with gesture recognition
Solution Approach 1:
The patent extracts and isolates relevant gesture motions from the complete set of user movements by applying gesture filters that specifically target desired body parts and motion patterns. Extraneous motions are filtered out during processing, maintaining measurement precision while managing complexity through selective extraction.
Solution Approach 2:
The gesture filters are dynamically configured based on the specific application and desired gestures, allowing the system to adapt to different motion recognition requirements. This dynamic configuration enables precise gesture recognition while maintaining manageable processing complexity through context-aware filtering.
Data Source
AI summary
A system may receive image data and capture motion with respect to a target in a physical space and recognize a gesture from the captured motion. It may be desirable to isolate aspects of captured motion to differentiate random and extraneous motions. For example, a gesture may comprise motion of a user's right arm, and it may be desirable to isolate the motion of the user's right arm and exclude an interpretation of any other motion. Thus, the isolated aspect may be the focus of the received data for gesture recognition. Alternately, the isolated aspects may be an aspect of the captured motion that is removed from consideration when identifying a gesture from the captured motion. For example, gesture filters may be modified to correspond to the user's natural lean to eliminate the effect the lean has on the registry of a motion with a gesture filter.