cs.CVApr 13, 2026

Product Review Based on Optimized Facial Expression Detection

Authors: Vikrant Chaugule, Abhishek D, Aadheeshwar Vijayakumar, Pravin Bhaskar Ramteke, Shashidhar G. Koolagudi

Organizations: National Institute of Technology Karnataka, Surathkal, Karnataka, India

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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.

Figures & tables

Fig. 1: Haar like feature
Fig. 2: Cascade of feature Classifiers
Fig. 3: Graph showing high sigma values require significantly more calculations per pixel
Fig. 4: flow chart of the proposed approach
Fig. 5: Corner Detection Theory
Fig. 6: Comparison on happy face
Fig. 7: Comparison on sad face
Fig. 8: Table showing time required for processing
Fig. 9: Graph showing time required for processing
Fig. 10: Table showing comparison of accuracy over previous algorithm
Fig. 11: Graph showing comparison of accuracy over previous algorithm
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Facial Expression Recognition

Facial Expression Recognition studies how computers infer emotion and facial actions from images and video.

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