Spatiotemporal Video Indexing for Multi-Camera Event Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle to effectively capture, analyze, and visualize vast volumes of sporting event data, failing to provide meaningful insights and tools for mining and presenting relevant information from video feeds.
Innovation Solution
A method involving spatiotemporal analysis of video feeds, using calibrated tracking and broadcast cameras to generate a spatio-temporal index, aligning video frames, and augmenting content with relevant information, enabling enhanced decision-making and entertainment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If video feeds from multiple cameras (broadcast and tracking) are combined, then comprehensive event coverage is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the video feeds into distinct broadcast video feed and tracking camera video feed components, processing each separately before integrating them through time-aligning and spatial-aligning operations. This segmentation allows complex multi-camera data to be handled through modular processing stages.
Solution Approach 2:
The patent introduces a spatio-temporal index as an intermediary data structure that mediates between the broadcast video feed and tracking camera video feed. This index contains aligned event data and serves as a bridge to integrate information from multiple camera sources without directly processing all raw data simultaneously.
2Measurement precision
If multiple video feeds are time-aligned and spatially-aligned, then event detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs time-aligning operations between broadcast video feed and tracking camera video feed before conducting event detection. This preliminary alignment ensures that events are detected with accurate temporal synchronization, improving detection accuracy while establishing a structured processing sequence.
Solution Approach 2:
The patent performs spatial-aligning operations to establish corresponding spatial locations between different video feeds before event detection. This preliminary spatial alignment enables accurate event localization across multiple cameras without requiring complex real-time alignment during detection.
3Loss of information
If spatio-temporal analysis is performed on video data, then meaningful insights are improved, but computational resources required increase
Solution Approach 1:
The patent extracts and isolates specific events from the video feeds using pattern recognition, then processes only these extracted events through spatio-temporal analysis. This extraction approach focuses computational resources on meaningful event data rather than processing entire video streams, improving insight quality while managing computational load.
Solution Approach 2:
The spatio-temporal index acts as an intermediary that pre-processes and structures video data into aligned event representations. This intermediary structure enables efficient spatio-temporal analysis by organizing data in advance, reducing the computational resources needed during actual insight generation.
Data Source
AI summary
A location in a video may be specified and content related to the location may be accessed. A method for accessing the related content may include receiving a reference to a pixel location in a frame of a video feed of a filmed occurrence and accessing a spatio-temporal index corresponding to the filmed occurrence. The spatio-temporal index may index information relating to events or objects of the filmed occurrence and corresponding pixel locations at which the events or the objects are detected in the video feed. The method may further include querying the spatio-temporal index using the pixel location to determine particular information of an indexed event or an indexed object and receiving the particular information wherein the particular information indicates at least one of spatial and temporal alignment parameters for aligning the indexed event with a corresponding event in at least one other video feed of the filmed occurrence.