Video Analysis System Mitigating Perspective Effects in Object Tracking
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Solution Overview
Problem
Current data visualization tools are inadequate for visualizing analysis data of moving objects in videos due to limitations such as the perspective effect, which leads to errors and inefficiencies in analysis.
Innovation Solution
A computer-implemented method and system that identifies and tracks moving objects in videos by determining track points and generating video analysis results, which are then visualized using static or dynamic heat maps or track maps, selectively analyzing frames based on frame rate and object location to mitigate perspective effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data visualization tools (static heat map, dynamic heat map, track map) are used to visualize moving objects in video, then visualization can be achieved, but perspective effect causes errors and reduces measurement precision
Solution Approach 1:
The patent changes the parameter of frame selection by introducing a frame rate parameter and selectively analyzing only certain frames based on the moving object's location and the frame rate, rather than analyzing all frames. This reduces the perspective effect impact while maintaining visualization accuracy.
Solution Approach 2:
The patent applies partial action by selectively analyzing only specific frames (based on frame rate and object location) rather than all frames in the video. This partial analysis reduces computational load and perspective effect errors while maintaining sufficient visualization accuracy.
2Loss of information
If all frames are analyzed to ensure complete tracking information, then tracking completeness is improved, but analysis time and computational resources increase
Solution Approach 1:
The patent introduces a frame rate parameter to control the density of frame analysis. By adjusting this parameter, the system can balance between tracking completeness and analysis time, selecting an optimal subset of frames to analyze based on the moving object's characteristics and video properties.
Solution Approach 2:
The patent implements partial action by analyzing only a selected subset of frames rather than all frames. The selection criteria include frame rate and moving object location, ensuring that critical tracking information is captured while minimizing unnecessary analysis and reducing overall processing time.
3Measurement precision
If frame rate is increased to capture more moving object positions, then tracking precision is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent uses the frame rate as a controllable parameter to adjust tracking precision. By selectively applying different frame rates based on moving object location and video characteristics, the system achieves optimal tracking precision while managing computational complexity effectively.
Solution Approach 2:
The patent applies partial action by analyzing only necessary frames at higher frame rates rather than all frames. The selection is based on moving object location and video properties, ensuring high tracking precision is achieved only where and when needed, thus reducing overall computational complexity.
Data Source
AI summary
The present disclosure relates to methods and systems for data visualization. The systems may perform the methods to obtain a video having a plurality of frames including a plurality of objects; identify a target object from the plurality of objects according to the plurality of frames; determine one or more track points of the target object, each of the one or more track points being corresponding to the target object in one of the plurality of frames; determine a first track of the target object based on the track points, the first track including at least one of the one or more track points of the target object; determine a second track of the target object based on the first track, the second track including at least one of the track points of the first track; generate a video analysis result by analyzing the second track; and visualize the video analysis result.