Impact Time Computation via Local Extreme Point Duration Tracking
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Solution Overview
Problem
Conventional methods for computing time-to-impact using image sensing require complex computations and large amounts of data, leading to high costs and inefficiencies, making them unsuitable for many applications.
Innovation Solution
A method that computes impact time by determining duration values for local extreme points in image frames, which are then used to estimate time-to-impact, reducing data requirements and enabling parallel processing on simpler hardware architectures like SIMD processors or NSIP processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods for computing impact time are used, then measurement precision is improved, but device complexity increases and cost efficiency deteriorates
Solution Approach 1:
The patent extracts only the essential information needed for impact time computation by identifying and tracking local extreme points (LEPs) in the image sequence. Instead of processing all image data or computing full optical flow fields, the method isolates and processes only the LEPs, which are sufficient to determine impact time. This extraction principle reduces the data volume and computational complexity while maintaining the necessary measurement precision.
Solution Approach 2:
The patent uses simple integer count values to represent duration values, creating a simplified copy of the temporal information rather than storing complete image sequences or complex motion vectors. Each LEP is associated with a simple counter that increments with each frame, creating a compact representation that preserves the essential timing information needed for impact time computation.
2Measurement precision
If conventional methods for computing impact time are used, then measurement precision is improved, but productivity deteriorates due to slow computation speed
Solution Approach 1:
The patent segments the image sequence processing into independent per-LEP operations. Each LEP is processed independently to compute its duration value, and these independent computations can be executed in parallel. This segmentation eliminates the need for complex sequential processing of entire image frames or optical flow fields, enabling faster computation while maintaining precision.
Solution Approach 2:
The patent performs partial action by computing impact time using only the LEPs rather than processing the entire image sequence or computing complete optical flow. This partial processing approach focuses computational resources on the essential elements (LEPs and their duration values) needed for impact time determination, achieving sufficient precision with reduced computation time.
3Measurement precision
If conventional methods for computing impact time are used, then measurement precision is improved, but loss of information increases due to heavy data requirements
Solution Approach 1:
The patent extracts only the critical temporal information needed for impact time computation by tracking LEPs and counting their duration. Instead of retaining or processing large amounts of image data, the method extracts just the essential timing information (duration values) associated with each LEP, minimizing information loss while maintaining computation accuracy.
Solution Approach 2:
The patent changes the parameter representation from complex image data or optical flow vectors to simple integer count values. Each LEP's temporal behavior is represented by a duration value (integer count), transforming the data into a compact form that preserves the essential information for impact time computation while dramatically reducing data volume.
4Device complexity
If simpler hardware architectures are used, then device complexity is reduced and cost efficiency is improved, but measurement precision deteriorates
Solution Approach 1:
The patent enables simpler hardware to perform impact time computation by designing an algorithm that naturally fits parallel processing architectures. The independent per-LEP computations can be executed simultaneously by simple processing elements, allowing the hardware to serve itself efficiently without requiring complex sequential processors. This self-service approach maintains measurement precision while utilizing simpler, more cost-effective hardware.
Solution Approach 2:
The patent segments the computation into independent per-LEP operations that can be distributed across multiple simple processing elements. Each processing element handles one or more LEPs independently, computing duration values and contributing to the overall impact time determination. This segmentation allows simple hardware to achieve the same measurement precision as complex hardware by distributing the computational task across multiple independent units.
Data Source
AI summary
Impact time between an image sensing circuitry and an object relatively moving at least partially towards, or away from, the image sensing circuitry can be computed. Image data associated with a respective image frame of a sequence (1 . . . N) of image frames sensed by said image sensing circuitry and which image frames are imaging said object can be received. For each one (i) of multiple pixel positions, a respective duration value (f(i)) indicative of a largest duration of consecutively occurring local extreme points in said sequence (1 . . . N) of image frames can be computed. A local extreme point is present in a pixel position (i) when an image data value of the pixel position (i) is a maxima or minima in relation to image data values of those pixel positions that are closest neighbors to said pixel position (i).