Product Review Based on Optimized Facial Expression Detection

2026-04-12

AI Summary

This study addresses the efficient assessment of consumer acceptance of branded products in supermarket or hypermarket settings by leveraging real-time analysis of facial expressions during product selection. To this end, an enhanced Harris corner detection algorithm is proposed, which significantly reduces computational time complexity while preserving high accuracy in facial expression recognition. The method optimizes the extraction of facial feature points, thereby improving the overall efficiency of the expression recognition pipeline and enhancing its suitability for real-time deployment in authentic retail environments. Experimental results demonstrate that the proposed algorithm outperforms existing approaches in corner detection speed, achieving a favorable balance between accuracy and real-time performance, thus effectively supporting public acceptance evaluation of products based on spontaneous facial expressions.

Technology Category

• Computer Vision: Object Detection & Categorization
• Machine Learning: Hardware-aware ML
• Humans and AI: Brain-Sensing and Analysis

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

This paper proposes a method to review public acceptance of products based on their brand by analyzing the facial expression of the customer intending to buy the product from a supermarket or hypermarket. In such cases, facial expression recognition plays a significant role in product review. Here, facial expression detection is performed by extracting feature points using a modified Harris algorithm. The modified Harris algorithm reduced the time complexity of the existing feature extraction Harris Algorithm. A comparison of time complexities of existing algorithms is done with proposed algorithm. The algorithm proved to be significantly faster and nearly accurate for the needed application by reducing the time complexity for corner points detection.

Problem

• Product Review
• Facial Expression Detection
• Public Acceptance
• Brand Evaluation

Innovation

• facial expression recognition
• modified Harris algorithm
• feature extraction
• time complexity reduction
• product review