Object Tracking via Optical Flow Motion Vectors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current object tracking systems face challenges in accurately correlating objects between video frames due to unreliable speed and accuracy of existing techniques, which often require significant computational resources not always available.
Innovation Solution
The use of representative motion information, determined through optical flow analysis, allows for efficient tracking of objects by identifying unique motion vectors and applying them across frames, reducing the need for constant feature detection in every frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional object tracking techniques are used to correlate objects between video frames, then object tracking can be performed, but the accuracy and reliability are insufficient and significant computational resources are required
Solution Approach 1:
The patent extracts only the essential motion information (optical flow vectors) from video frames rather than processing complete feature sets. By isolating and utilizing only the motion vectors that represent object movement between frames, the system achieves reliable tracking with reduced computational complexity, directly resolving the contradiction between tracking reliability and device complexity
Solution Approach 2:
The patent creates simplified copies of motion information by generating synthetic video sequences that replicate only the essential motion patterns from original video frames. These copied motion representations can be processed more efficiently while maintaining tracking accuracy, thereby reducing the computational resources needed for reliable object correlation
2Measurement precision
If feature detection is performed in every video frame to track objects, then tracking accuracy can be maintained, but processing speed decreases and computational resources increase
Solution Approach 1:
The patent implements periodic feature detection only at selected intervals rather than in every frame. By performing comprehensive feature detection periodically and using optical flow interpolation between these intervals, the system maintains measurement precision while significantly improving processing speed and reducing computational load
Solution Approach 2:
The patent performs preliminary optical flow analysis on selected frames to predict object positions in intermediate frames. By pre-calculating motion vectors and applying them to generate predicted positions, the system maintains accurate tracking without requiring full feature detection in every frame, thus balancing precision and productivity
Data Source
AI summary
Apparatuses, systems, and techniques are presented to track objects represented in images or video data. In at least one embodiment, motion of one or more objects within a plurality of digital images is determined based, at least in part, on flow information corresponding to the one or more objects.