Unified Bounding Box Search Term Extraction
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Solution Overview
Problem
Conventional mobile visual search systems struggle to recognize multiple content types, such as barcodes, OCR, and speech-to-text in real-time, due to fragmented bounding box detection, leading to erroneous results and the need for manual textual entry for information retrieval.
Innovation Solution
A system that utilizes a context/content processing platform to preprocess sensor data, merge bounding boxes, and integrate multi-modal inputs like GPS, camera, and audio sensors to extract search terms, enabling real-time online textual searches with minimal textual entry through an augmented reality browser.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional mobile visual search systems use fragmented bounding box detection for multiple content types, then device complexity is reduced, but measurement precision and reliability deteriorate leading to erroneous results
Solution Approach 1:
The patent merges fragmented bounding box detections into unified bounding boxes that encompass multiple content types (barcodes, OCR text, speech-to-text regions). This consolidation integrates previously separate detection processes into a cohesive framework, resolving the contradiction by maintaining system simplicity while achieving accurate multi-content recognition through unified spatial boundaries.
2Ease of operation
If conventional systems require manual textual entry for information retrieval, then ease of operation deteriorates, but loss of information is reduced
Solution Approach 1:
The system performs automatic search term extraction from sensor data (images, audio, GPS context) without requiring manual user input. The device serves itself by autonomously identifying content types, generating bounding boxes, and formulating search queries from environmental data, thereby eliminating the trade-off between ease of operation and information accuracy.
3Productivity
If the system integrates multi-modal sensor data processing, then productivity improves through real-time search, but device complexity increases
Solution Approach 1:
The patent segments the complex multi-modal processing task into distinct functional modules: sensor data acquisition, content type classification, bounding box generation and merging, search term extraction, and query formulation. This segmentation allows real-time processing productivity while managing complexity through modular architecture, where each component handles a specific aspect of the data flow independently.
4Adaptability or versatility
If fragmented bounding box detection is used for multiple content types, then adaptability improves for handling diverse data modes, but measurement precision deteriorates
Solution Approach 1:
The system implements a universal bounding box framework that handles multiple content types (barcodes, OCR text, speech-to-text regions) through a single integrated process. This multi-functional approach maintains adaptability for diverse data modes while improving precision by applying consistent detection and merging logic across all content types, eliminating the need for separate specialized processes.
Data Source
AI summary
An approach is provided for conducting a search based on an extraction of a search term from available sensor data. The approach involves determining sensor data associated with at least one device, the sensor data determined from among a plurality of available data modes. The approach also involved processing and/or facilitating a processing of the sensor data to cause, at least in part, an extraction of one or more search terms for at least one query. The approach further involves determining one or more results of the at least one query based, at least in part, on context information associated with the at least one device, user profile information associated with the at least one device, or a combination thereof.