Virtual Camera Path Alignment with Action Tracking
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Solution Overview
Problem
Existing systems face challenges in efficiently inserting pre-existing virtual camera paths into virtual environments, particularly in live sports broadcasting, due to variations in scenes and events, requiring skilled operators to adapt camera paths to capture target objects effectively.
Innovation Solution
A method and system for determining a virtual camera path by configuring an action path in video data, selecting a template camera path, and aligning the template focus path with the action path, transforming the camera path based on alignment to ensure accurate and aesthetically pleasing captures of events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a pre-existing virtual camera path is inserted into the scene, then the time required to produce a replay is reduced, but the target object may not be captured in the desired manner due to scene and event variations
Solution Approach 1:
The system pre-defines multiple camera paths with associated focus paths in advance. During replay production, these pre-configured paths are automatically selected and applied based on the detected action in the scene, eliminating the need for manual camera path creation while ensuring the target object is captured correctly through the pre-validated focus path relationships.
Solution Approach 2:
The system dynamically adjusts the camera path selection and parameters based on the detected action path in the scene. The focus path is automatically aligned with the detected action, allowing the system to adapt pre-existing camera paths to different scenes and events while maintaining reliable target object capture.
2Reliability
If a user manually poses the virtual camera and defines parameters, then the target object can be captured, but the process is time-consuming and requires skilled operators
Solution Approach 1:
The system automatically detects the action path in the scene and self-adjusts the camera path parameters by aligning the focus path with the detected action. This eliminates the need for skilled operators to manually pose the camera and define parameters, while still achieving accurate target object capture through automated path alignment.
Solution Approach 2:
The system replaces manual mechanical camera operation with automated computer vision and path alignment algorithms. The action detection and focus path alignment mechanisms substitute for skilled human operators, automatically determining the appropriate camera positioning and parameters based on the detected scene action.
3Ease of operation
If the virtual camera follows a pre-defined path, then the operation is simplified, but there is little control to ensure the target object is captured as the event progresses
Solution Approach 1:
The system pre-defines focus paths associated with each camera path that specify the intended target object trajectory. During operation, the system detects the actual action path and aligns it with the pre-defined focus path, ensuring the target object is captured correctly while maintaining the simplicity of using pre-defined camera paths.
Solution Approach 2:
The system uses feedback from action detection to dynamically align the focus path with the detected action path. This feedback mechanism ensures that the simplified pre-defined camera paths still achieve reliable target object capture by automatically adjusting the focus based on the actual scene content.
4Reliability
If different camera paths are created for each unique event, then the target object is captured accurately, but the complexity and time required increases significantly
Solution Approach 1:
The system creates a library of universal camera paths with associated focus paths that can be applied to multiple different events and scenes. The focus path alignment mechanism allows these universal templates to adapt to specific events automatically, eliminating the need to create separate camera paths for each unique event while maintaining accurate target object capture.
Solution Approach 2:
The system changes the parameters of pre-defined camera paths dynamically based on the detected action. By adjusting the focus path alignment and camera parameters according to the detected action path, the system adapts universal camera paths to specific events without requiring manual creation of new paths, reducing complexity while maintaining accuracy.
Data Source
AI summary
A computer-implemented system and method of determining a virtual camera path. The method comprises determining an action path in video data of a scene, wherein the action path includes at least two points, each of the two points defining a three-dimensional position and a time in the video data; and selecting a template for a virtual camera path, the template camera path including information defining a template camera path with respect to an associated template focus path. The method further comprises aligning the template focus path with the determined action path in the scene and transforming the template camera path based on the alignment to determine the virtual camera path.