Introducing AI to Undergraduate Students via Computer Vision Projects

Authors

  • Kaiman Zeng Arkansas Tech University
  • Yancheng Li Arkansas Tech University
  • Yida Xu Arkansas Tech University
  • Di Wu Arkansas Tech University
  • Nansong Wu Arkansas Tech University

DOI:

https://doi.org/10.1609/aaai.v32i1.11403

Keywords:

Landmark recognition, Feature detection, Feature description, SURF

Abstract

Computer vision, as a subfield in the general artificial intelligence (AI), is a technology can be visualized and easily found in a large number of state-of-art applications. In this project, undergraduate students performed research on a landmark recognition task using computer vision techniques. The project focused on analyzing, designing, configuring, and testing the two core components in landmark recognition: feature detection and description. The project modeled the landmark recognition system as a tour guide for visitors to the campus and evaluated the performance in the real world circumstances. By analyzing real-world data and solving problems, student’s cognitive skills and critical thinking skills were sharpened. Their knowledge and understanding in mathematical modeling and data processing were also enhanced.

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Published

2018-04-27

How to Cite

Zeng, K., Li, Y., Xu, Y., Wu, D., & Wu, N. (2018). Introducing AI to Undergraduate Students via Computer Vision Projects. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11403