Product Review Based on Optimized Facial Expression Detection

TL;DR

This paper introduces a facial expression detection method using a modified Harris algorithm to analyze customer reactions for product reviews, emphasizing speed and accuracy improvements.

Contribution

A novel modified Harris algorithm for facial feature detection that reduces time complexity and enhances speed for product review applications.

Findings

The modified Harris algorithm is significantly faster than existing methods.

The proposed method achieves nearly accurate facial expression detection.

Time complexity is reduced for corner point detection in facial features.

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.