通过优化角点检测加速面部表情分析，提升商品接受度评估效率
Product Review Based on Optimized Facial Expression Detection
- 用改进的Harris算法提取面部特征点，降低计算复杂度
- 新算法在角点检测上速度显著提升，接近原有精度
- 适合需要实时表情分析的零售场景应用
本文提出一种基于顾客面部表情分析的商品接受度评估方法，针对超市或大型商场中消费者购买意图的场景。面部表情识别在产品评价中起关键作用。采用改进的Harris算法进行特征点提取，该算法降低了现有特征提取Harris算法的时间复杂度。对现有算法与所提算法的时间复杂度进行了对比，结果表明所提算法在角点检测中显著更快速，且精度满足实际应用需求。
原文摘要 · Abstract (English)
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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