Product review based on optimized facial expression detection

Vikrant Chaugule, D. Abhishek, Aadheeshwar Vijayakumar, P. B. Ramteke, S. Koolagudi
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引用次数: 5

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.
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基于优化面部表情检测的产品评审
本文提出了一种通过分析打算从超市或大卖场购买产品的顾客的面部表情来评估公众对品牌产品的接受程度的方法。在这种情况下,面部表情识别在产品审查中起着重要的作用。在这里,面部表情检测是通过使用改进的Harris算法提取特征点来完成的。改进的Harris算法降低了现有特征提取Harris算法的时间复杂度。对现有算法的时间复杂度进行了比较。该算法通过降低角点检测的时间复杂度,大大提高了检测速度和精度。
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