Particle Filter Resampling via Cumulative Weight Thresholds
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Solution Overview
Problem
In object tracking systems using particle filters, increasing the number of particles for detection accuracy leads to a significant computational burden and degraded system throughput due to the increased processing load.
Innovation Solution
An image processing apparatus that uses a predetermined number of particles and performs resampling by calculating cumulative weights and comparative values to efficiently reselect particles, reducing the need for a large-scale selector or pseudo-random number generation, thereby decreasing processing load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of particles is increased to improve detection accuracy, then detection accuracy improves, but computational burden increases significantly
Solution Approach 1:
The patent changes the parameter of particle selection from traditional weight-based proportional selection to a method based on cumulative weight thresholds. By setting a threshold value and selecting particles whose cumulative weight exceeds this threshold, the system achieves effective resampling with fewer computational operations, resolving the contradiction between detection accuracy and computational burden
Solution Approach 2:
The patent extracts and removes the computationally intensive pseudo-random number generation and large-scale selector components from the particle filter system. By using a deterministic threshold-based selection method instead, it eliminates the need for complex random number generation while maintaining particle selection effectiveness, thus reducing computational burden
2Measurement precision
If the number of particles is increased to improve detection accuracy, then detection accuracy improves, but system throughput decreases
Solution Approach 1:
The patent changes the selection parameter from continuous weight-based proportional sampling to discrete threshold-based selection. This parameter change enables faster particle selection operations that do not require processing all particles through complex weight calculations, thereby improving system throughput while maintaining detection accuracy through effective particle resampling
3Measurement precision
If a large-scale selector is used for particle resampling, then particle selection accuracy improves, but processing load increases
Solution Approach 1:
The patent extracts and eliminates the large-scale selector component from the particle filter architecture. By replacing it with a simple threshold comparison mechanism that operates on cumulative weights, the system achieves particle selection without the computational overhead of large-scale selectors, reducing processing load while maintaining selection accuracy
Solution Approach 2:
The patent substitutes the mechanical/computational system of large-scale selectors and pseudo-random number generators with a mathematical threshold-based selection system. This substitution replaces complex computational mechanics with simpler arithmetic operations on cumulative weights, reducing processing load while preserving particle selection effectiveness
Data Source
AI summary
An image processing apparatus is configured to perform processing of detecting an object by using a predetermined number of sample points referred to as particles, the processing including: executing a detection processing configured to calculate a weight for each of the particles, and detect the object by using the calculated weights; and executing a resampling processing configured to assign a particle number to each of the predetermined number of particles, calculate, for each particle, a comparative value by multiplying an average of the weights of the predetermined number of particles by the particle number, calculate, for each particle, a cumulative weight by adding the particle's own weight to the weights of all the particles assigned with the respective particle numbers smaller than the particle's own particle number, and perform a reselection process that executes reselection on the particles of all the particle numbers.