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Product review based on optimized facial expression detection

机译:基于优化的面部表情检测的产品评论

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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.
机译:本文提出了一种方法,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,来评估其产品品牌对公众的接受程度。在这种情况下,面部表情识别在产品评论中起着重要作用。这里,通过使用改进的哈里斯算法提取特征点来执行面部表情检测。改进的哈里斯算法降低了现有特征提取哈里斯算法的时间复杂度。现有算法时间复杂度的比较是通过提出的算法完成的。通过减少角点检测的时间复杂度,该算法对于所需的应用程序被证明明显更快,几乎准确。

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