Image Analytics: A Consolidation of Visual Feature Extraction Methods

Xiaohui Liu, Fei Liu, Yijing Li, Huizhang Shen, Eric T.K. Lim, Chee-Wee Tan*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Revolutionary advances in machine and deep learning techniques within the field of computer field have dramatically expanded our opportunities to decipher the merits of digital imagery in the business world. Although extant literature on computer vision has yielded a myriad of approaches for extracting core attributes from images, the esotericism of the advocated techniques hinders scholars from delving into the role of visual rhetoric in driving business performance. Consequently, this tutorial aims to consolidate resources for extracting visual features via conventional machine and/or deep learning techniques. We describe resources and techniques based on three visual feature extraction methods, namely calculation-, recognition-, and simulation-based. Additionally, we offer practical examples to illustrate how image features can be accessed via open-sourced python packages such as OpenCV and TensorFlow.
Original languageEnglish
JournalJournal of Management Analytics
Issue number4
Pages (from-to)569-597
Number of pages29
Publication statusPublished - Dec 2021

Bibliographical note

Published online: 24 Nov 2021.


  • Image analytics
  • Attribute extraction
  • Computer vision
  • Deep learning
  • Python

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