Multi-Level Abstraction Ladder for Image Object Identification
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Solution Overview
Problem
Existing methods for identifying objects and activities in electronic imagery face challenges in accurately organizing pixels into meaningful groups, particularly in resolving ambiguity and capturing movement and shape information across varying resolutions and fields of view.
Innovation Solution
The method involves a multi-level abstraction ladder for analyzing pixels, gradient sets, and curve primitives, using Bézier curves and video schematics to organize image elements into descriptive data, and a multi-point camera system with steerable resolution to enhance feature extraction and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixels are organized into meaningful groups using known analytical processes, then object identification is enabled, but visual ambiguity cannot be resolved and movement information is lost
Solution Approach 1:
The patent segments the image analysis process into multiple levels of abstraction (pixels → gradient sets → curve primitives → object features). Each level processes specific types of information independently, allowing movement data to be preserved through temporal segmentation across video frames while shape information is preserved through spatial segmentation into gradient and curve representations.
Solution Approach 2:
The patent adds temporal dimension to the analysis by processing video sequences across multiple frames. Movement information is captured by analyzing pixel group changes across time, while shape information is maintained through spatial gradient and curve representations. This multi-dimensional approach resolves ambiguity by providing both spatial and temporal context.
2Measurement precision
If high resolution is used throughout the image, then feature extraction accuracy improves, but data processing complexity and computational cost increase
Solution Approach 1:
The patent applies different levels of analysis quality to different regions and features. High-resolution detailed analysis (gradient sets, curve primitives) is applied locally to regions containing objects of interest, while broader contextual areas use lower-resolution pixel grouping. This local quality approach maintains feature extraction accuracy for critical elements while reducing overall computational complexity.
Solution Approach 2:
The patent segments the image into multiple abstraction levels, where each level processes data at appropriate resolution. The pixel level handles broad spatial relationships, gradient sets capture local intensity variations, and curve primitives represent object boundaries. This hierarchical segmentation allows efficient processing by matching computational effort to the information needs of each analysis level.
3Measurement precision
If multiple levels of abstraction are used to organize image elements, then object and activity identification improves, but processing time increases
Solution Approach 1:
The patent performs preliminary organization of pixels into gradient sets and curve primitives before full object identification. This preliminary action creates structured intermediate representations that capture essential shape and boundary information, making subsequent object and activity recognition more efficient and accurate while reducing the computational burden of analyzing raw pixel data.
Solution Approach 2:
The patent maintains continuous processing across video frames by tracking pixel groups, gradient sets, and curve primitives through time. This continuity allows the system to leverage temporal information for improved identification accuracy while optimizing processing by building upon previous frame analyses rather than重新 analyzing each frame independently.
Data Source
AI summary
Elements of an electronic image are organized into groups to obtain descriptive data associated with the electronic image. A wide field view of the electronic image is obtained from a first component and a higher resolution image of a selected portion of the wide field view of the electronic image is obtained from a second component to resolve ambiguity associated the selected portion of the wide field view of the electronic image. At least one primitive is formed using pixels of the electronic image, where the primitive is a curve primitive or a region primitive. The at least one primitive is analyzed using at least one level in a ladder of abstraction to organize elements of the electronic image into groups from which descriptive data can be obtained about at least one of objects or activities associated with the electronic image.