Object Tracking Region Filtering for Noise Interference
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Solution Overview
Problem
Existing object tracking systems face challenges in accurately tracking objects in varying environmental conditions and environments with unexpected signals, such as rain or snow, which generate strong noise signals that interfere with the tracking process.
Innovation Solution
A method and computing apparatus for managing object tracking in a three-dimensional environment by defining regions within the field of view of an electromagnetic sensor and applying specific region tracking conditions to filter and evaluate observations and paths, thereby reducing computational and memory resources required for tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed noise threshold or adaptive method is used to track objects, then the tracking program can distinguish signals from tracked objects from other signals, but strong signals from other objects or environmental conditions (traffic, cars, headlights, rain, snow) interfere with tracking accuracy
Solution Approach 1:
The field of view is divided into multiple regions, each with its own tracking conditions. This segmentation allows different parts of the image to be processed with different criteria, reducing the impact of strong signals in specific regions while maintaining tracking accuracy in other regions.
Solution Approach 2:
Different tracking conditions are applied to different regions based on their specific characteristics. Each region can have customized parameters for observation evaluation, allowing the system to adapt to local environmental conditions and minimize the effect of regional noise sources.
2Measurement precision
If all observations and paths are evaluated in continued tracking, then tracking accuracy is maintained, but computational and memory resources are excessively consumed
Solution Approach 1:
By dividing the field of view into regions and applying region-specific tracking conditions, the system reduces the total number of observations that need to be fully evaluated. Observations in regions with restrictive conditions can be quickly filtered out, reducing computational load while maintaining accuracy for relevant tracks.
Solution Approach 2:
The system applies selective evaluation where only certain observations meeting specific region tracking conditions undergo full evaluation. This partial action approach reduces overall computational resources consumed while ensuring that potentially valid tracks receive thorough assessment.
Data Source
AI summary
A method and a computing apparatus for managing tracking of an object moving in a three-dimensional environment are disclosed. The computing apparatus determines that an observation relating to the object matches a region. In an evaluation action, evaluating whether the observation and/or the path fulfills a region tracking condition of the region or not. The computing apparatus retains, based on the evaluation action, the observation and/or the path in continued tracking of the object. Alternatively, the computing apparatus discards, based on the evaluation action, the observation and/or the path from continued tracking of the object. Corresponding computer program(s) and computer program carrier(s) are also disclosed.