Image-Based Command Classification for Automated Task Generation
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Solution Overview
Problem
Conventional productivity tools require extensive user interaction and computational resources to determine tasks from images, failing to leverage image data features and context, leading to user frustration and inefficient battery usage.
Innovation Solution
A computer system infers commands from images, extracting alphanumeric and non-alphanumeric features to generate tasks and task entities, reducing the need for manual user input and computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional productivity tools require extensive user interaction to determine tasks from images, then task determination accuracy can be maintained through manual input, but user frustration increases and productivity decreases
Solution Approach 1:
The system automatically extracts image data features and determines tasks without requiring user interaction. The computer system performs self-service by autonomously analyzing the image, extracting relevant features, inferring commands, and generating tasks, eliminating the need for manual user input while maintaining high productivity
Solution Approach 2:
The patent replaces the mechanical interaction system (manual user inputs) with an automated image analysis system. Instead of requiring users to manually input task details, the system uses image data extraction and command inference to automatically determine tasks, substituting human interaction with computational processing
2Measurement precision
If conventional tools process images with extensive computational resources, then comprehensive task analysis can be achieved, but battery usage becomes inefficient
Solution Approach 1:
The system extracts only the necessary image data features required for task determination rather than processing the entire image comprehensively. By selectively extracting relevant features (such as text regions, objects, or specific patterns) and using them for command inference, the system achieves accurate task determination while minimizing computational resource consumption and battery usage
Solution Approach 2:
The patent applies partial action by performing only the necessary image processing steps required for task determination. Instead of comprehensive image analysis, the system extracts specific image data features and processes only what is needed to infer commands and generate tasks, reducing overall computational load and energy consumption while maintaining sufficient accuracy
3Productivity
If the system automatically generates tasks from images with minimal user input, then productivity increases and user interaction decreases, but the complexity of the system increases
Solution Approach 1:
The system employs a multi-functional architecture where a single integrated pipeline performs multiple functions: image data extraction, feature analysis, command inference, and task generation. This universal system handles various types of images and tasks through a unified approach, managing complexity through functional integration rather than separate specialized components for each operation
Data Source
AI summary
Provided are methods, systems, and computer storage media for determining a command (e.g., intent) of an image based on image data features. A task associated with the determined command is generated based on a portion of the image data features. Task entities corresponding to the task are determined. The task and the corresponding task entities are generated and configured for use in a computer productivity application. Accordingly, present embodiments provide an improved technique for generating command-specific tasks and task entities that may be integratable for use in a computer productivity application to enhance functionality of a computer productivity application and reduce computational resources utilized by manually creating these tasks and task entities.