Object Area Scaling Ratio Estimation Using Motion Vectors
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Solution Overview
Problem
Current methods for estimating the scaling ratio of objects in video image sequences, especially for irregular shapes, lack accuracy and require complex reference template construction or are limited to decoded images, failing to effectively utilize motion information.
Innovation Solution
A method that determines whether an object is stationary, generates a motion direction histogram, calculates the area scaling ratio by evaluating directed straight lines through the object's centroid, and computes length scaling ratios based on motion vector projections, allowing for accurate estimation of area scaling ratios even for irregularly shaped objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If blocking boundary artifact pixels are used to detect object boundaries and calculate scaling ratio, then the method is simple to implement, but the accuracy is reduced because blocking boundary artifacts do not always correspond to actual object boundaries
Solution Approach 1:
The patent extracts and utilizes motion vectors from video encoding processes, which inherently contain accurate object boundary information. By taking out the motion vector data that already encodes boundary information, the method avoids the need to use blocking boundary artifacts while maintaining accuracy.
Solution Approach 2:
The patent introduces motion vectors as an intermediary element that bridges the gap between simple implementation and accurate measurement. Motion vectors serve as a mediator that provides both ease of calculation and accurate object boundary representation, resolving the contradiction between simplicity and precision.
2Measurement precision
If scaling ratio is calculated by measuring displacements in x and y directions independently based on motion vectors, then rectangular objects can be estimated with high accuracy, but accuracy deteriorates for irregularly shaped objects
Solution Approach 1:
The patent creates a universal method that works for both rectangular and irregularly shaped objects by using motion vectors along object boundaries. This approach generalizes the scaling ratio calculation to handle diverse object shapes while maintaining high accuracy, making the method adaptable to various object types.
Solution Approach 2:
The patent transitions from independent x and y displacement measurements to a boundary-based approach that considers the dimensional relationship along the object perimeter. By measuring motion vectors along the boundary curve and integrating them, the method captures the true scaling behavior regardless of object shape complexity.
3Measurement precision
If reference template construction is used to determine scale factor, then accurate scaling ratio can be obtained, but the device complexity increases due to the need to construct and maintain reference templates
Solution Approach 1:
The patent enables the system to self-determine scaling ratios using motion vectors that are already available from the video encoding process. By utilizing existing motion compensation data, the method eliminates the need for external reference templates while maintaining accurate scaling measurements.
Solution Approach 2:
The patent changes the approach from template-based parameter matching to direct motion vector utilization. By transforming the problem from comparing scaled images with templates to analyzing motion vector magnitudes and directions, the method achieves accurate scaling without the complexity of template construction and maintenance.
4Ease of operation
If motion vectors are used to detect object movement, then the method is simple and utilizes available video information, but the scaling ratio cannot be calculated
Solution Approach 1:
The patent uses more motion vector information than just presence/absence of movement. By analyzing the magnitude and direction of motion vectors along object boundaries, the method extracts scaling ratio data that was previously unused, converting partial motion detection into complete scaling analysis.
Solution Approach 2:
The patent creates a feedback loop where motion vectors, initially used only for movement detection, are fed back into the scaling ratio calculation process. By reutilizing the same motion vector data to determine both movement and scaling, the method recovers the lost scaling information without requiring additional complex processing.
Data Source
AI summary
This invention discloses a method for object tracking, including determination of an area scaling ratio of the object in a video image sequence. In one embodiment, a centroid of the object is determined. One or more directed straight lines are selected, each passing through the centroid, extending from an end of the object's boundary to an opposite end thereof, and having a direction that is upward. A length scaling ratio for each directed straight line is determined by: determining a motion vector for each selected pixel on the line; computing a scalar component of the motion vector projected onto the line; estimating a change of the line's length according to the scalar components obtained for all pixels; and determining the length scaling ratio according to the change of the line's length. The area scaling ratio is computed based on the length scaling ratios for all directed straight lines.