Product review based on optimized facial expression detection

dc.contributor.authorChaugule, V.
dc.contributor.authorAbhishek, D.
dc.contributor.authorVijayakumar, A.
dc.contributor.authorRamteke, P.B.
dc.contributor.authorKoolagudi, S.G.
dc.date.accessioned2026-02-06T06:38:46Z
dc.date.issued2017
dc.description.abstractThis 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. © 2016 IEEE.
dc.identifier.citation2016 9th International Conference on Contemporary Computing, IC3 2016, 2017, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/IC3.2016.7880213
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/31874
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectEmotion Detection
dc.subjectFeature Extraction
dc.subjectGaussian Filter
dc.subjectProduct Review
dc.titleProduct review based on optimized facial expression detection

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