Predicate logic based image grammars for complex visual pattern recognition

This invention describes a computer system that recognizes complex visual patterns in images by using a set of logical rules, similar to a grammar. It processes image data to find basic features, then applies these rules, which are designed to handle uncertainty, to identify larger patterns like people or structures. The system can also learn and optimize these rules automatically to improve its accuracy.

Why it matters: In 2010, robust image feature detection was a significant challenge. Today, deep learning has dramatically advanced the ability to extract features and recognize basic patterns from images, making the initial detection steps much more robust. This invention's symbolic logic and uncertainty framework could now be used to build upon these robust deep learning outputs, providing structured, interpretable reasoning for complex visual patterns and activities.

Status: ExpiredProtection ended and was never renewed
How hard to build: SpecializedSoftware logic, computer vision, rule optimization

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