Automated Brand Impact Quantification in Digital Media
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Solution Overview
Problem
Enterprises face challenges in quantifying the quantity and quality of brand representation during events, as manual audits of digital media recordings are time and resource intensive, and existing methods lack efficiency in evaluating brand impact from intermittent and varying quality logo appearances.
Innovation Solution
A computer-implemented method for unsupervised aspect extraction from digital media, which processes frames to determine pixel weights, quality, and quotients, calculating an impact indicator for logos based on frame and media size, using distributions like bivariate normal and multimodal distributions, and bias values to assess brand impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual audit of digital media is conducted to evaluate brand impact, then measurement precision of brand representation is improved, but productivity and time consumption deteriorate
Solution Approach 1:
The patent replaces the manual mechanical auditing process with an automated computer-implemented system that processes digital media frames. The system uses algorithms to detect logos, calculate pixel quotients, and determine impact indicators automatically, eliminating the need for human auditors to manually review each frame while maintaining measurement precision through systematic computational analysis.
Solution Approach 2:
The system performs self-service by automatically analyzing digital media without human intervention. It independently executes frame processing, logo detection, quality assessment, and impact calculation, making the evaluation process autonomous and significantly improving productivity while preserving measurement accuracy through consistent algorithmic application.
2Measurement precision
If comprehensive analysis of all frames is performed to ensure accurate brand impact assessment, then measurement precision is improved, but use of computing resources deteriorates
Solution Approach 1:
The patent applies local quality by focusing computational resources only on relevant portions of each frame. Instead of analyzing entire frames uniformly, the system identifies and analyzes only the logo regions and surrounding areas that contribute to brand impact, calculating pixel quotients selectively in these localized regions to reduce overall computing resource consumption while maintaining assessment accuracy.
Solution Approach 2:
The system segments the digital media into individual frames and further segments each frame into relevant logo regions. This segmentation allows the processing system to handle manageable portions separately, applying specific analysis only where needed, thereby reducing total computing resource requirements while preserving comprehensive brand impact assessment through systematic frame-by-frame and region-by-region analysis.
3Measurement precision
If detailed pixel-level analysis is conducted for each frame to improve quality assessment, then measurement precision is improved, but device complexity and processing time deteriorate
Solution Approach 1:
The patent employs parameter changes by transforming detailed pixel-level data into a simplified pixel quotient metric. The system calculates pixel quotients that combine multiple quality parameters (such as logo visibility, contrast, and prominence) into a single representative value for each pixel, reducing the complexity of analysis while maintaining precise quality assessment through this transformed parameter representation.
Data Source
AI summary
Methods, systems, and computer-readable storage media for receiving a set of frames, each frame being provided as a digital image that depicts a portion of an event and a logo associated with a brand, for each frame in the set of frames, and for each pixel in a frame: determining a weight of the pixel based on a distribution assigned to the frame, providing a quality of the logo depicted in the frame, and calculating a pixel quotient based on the weight and the quality, for each frame in the set of frames: determining a frame quotient at least partially based on a sum of all pixel quotients for the frame, and determining an impact indicator for the logo based on a total size of digital media comprising the set of frames and a sum of frame quotients of the frames in the set of frames.