Split-Screen Pairing via Dual-Camera Exposure Segmentation
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Solution Overview
Problem
Existing gaming technologies face challenges in efficiently and intuitively associating controllers with users, particularly in multi-player interactive environments, often requiring cumbersome initialization procedures and struggling with accurate tracking in varying light conditions.
Innovation Solution
The use of dual cameras with different exposure settings and resolutions, along with a microphone array, to capture and analyze images and sound, enabling the identification and tracking of users and controllers through facial recognition and illuminated tracking features, allowing for precise pairing and interaction in interactive applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single camera is used to capture images in gaming environments, then the device complexity is low, but the tracking accuracy of illuminated objects and user identification is insufficient in varying light conditions
Solution Approach 1:
The imaging system is segmented into multiple cameras with different exposure settings. A first camera captures images at a first exposure setting for general scene detection, while a second camera captures images at a second exposure setting for illuminated object tracking. This segmentation allows each camera to specialize in specific tracking tasks, improving overall measurement precision without requiring a single complex camera system.
Solution Approach 2:
Different regions of the gaming environment are captured with different quality parameters. The first camera optimizes for capturing user faces and general environment at higher exposure, while the second camera optimizes for capturing illuminated controller features at lower exposure. This local quality differentiation ensures that each tracking target receives optimal imaging conditions.
2Measurement precision
If multiple cameras with different exposure settings are used, then the tracking accuracy of illuminated objects and user identification improves, but the device complexity increases
Solution Approach 1:
The multiple-camera system serves multiple functions simultaneously: user identification, controller tracking, and environment monitoring. By making the imaging system multi-functional, the increased device complexity is justified by the comprehensive improvement in identification accuracy across different target types and lighting conditions.
Solution Approach 2:
The system changes imaging parameters (exposure settings) to match different tracking requirements. The first camera uses higher exposure for user identification in varied lighting, while the second camera uses lower exposure to enhance illuminated object visibility. This parameter differentiation resolves the contradiction by optimizing each camera for its specific function.
3Productivity
If traditional controller-user association methods are used, then the initialization process is simple, but the efficiency of controller-user association is low in multi-player environments
Solution Approach 1:
The manual controller-user association process is replaced with an automated optical recognition system. The camera system automatically detects illuminated controller features and user faces, then pairs them through image analysis and pattern recognition algorithms. This substitution of mechanical pairing with automated vision-based association dramatically improves productivity in multi-player environments.
Solution Approach 2:
The system performs self-service by automatically identifying and pairing controllers with users without requiring manual intervention. The image capture device autonomously analyzes the gaming environment, identifies illuminated controllers and user faces, determines spatial relationships, and establishes associations automatically, enabling rapid multi-player setup.
4Measurement precision
If illuminated tracking features on controllers are used, then the tracking accuracy improves, but the system performance degrades in dark environments
Solution Approach 1:
The first camera acts as an intermediary that captures ambient light information and user face data in dark environments, while the second camera captures illuminated controller features. The system combines information from both cameras, using the first camera to compensate for low ambient illumination and the second camera to track illuminated features, thereby maintaining tracking precision across varying illumination conditions.
Data Source
AI summary
A method for managing multi-player interactivity with an interactive application is provided, including the following operations: determining locations of a first controller, a second controller, a first user, and a second user; pairing the first controller to the first user based on the location of the first controller and the location of the first user; pairing the second controller to the second user based on the location of the second controller and the location of the second user; presenting a split-screen view of the interactive application, wherein presenting the split-screen view includes setting positions of a first view and a second view within the split-screen view based on one or more of the locations of the first user, the second user, the first controller, or the second controller.