ML Anthology

Recognizing Locations with Google Glass: A Case Study

Hani Altwaijry, Mohammad Moghimi, Serge J. Belongie
WACV 2014 pp. 167-174
doi:10.1109/WACV.2014.6836105 /wacv/2014/altwaijry2014wacv-recognizing/

Abstract

Wearable computers are rapidly gaining popularity as more people incorporate them into their everyday lives. The introduction of these devices allows for wider deployment of Computer Vision based applications. In this paper, we describe a system developed to deliver users of wearable computers a tour guide experience. In building our system, we compare and contrast different techniques towards achieving our goals. Those techniques include using various descriptor types, such as HOG, SIFT and SURF, under different encoding models, such as holistic approaches, Bag-of-Words, and Fisher Vectors. We evaluate those approaches using classification methods including Nearest Neighbor and Support Vector Machines. We also show how to incorporate information external to images, specifically GPS, to improve the user experience.

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Cite

Text

Altwaijry et al. "Recognizing Locations with Google Glass: A Case Study." IEEE/CVF Winter Conference on Applications of Computer Vision, 2014. doi:10.1109/WACV.2014.6836105

Markdown

[Altwaijry et al. "Recognizing Locations with Google Glass: A Case Study." IEEE/CVF Winter Conference on Applications of Computer Vision, 2014.](https://mlanthology.org/wacv/2014/altwaijry2014wacv-recognizing/) doi:10.1109/WACV.2014.6836105

BibTeX

@inproceedings{altwaijry2014wacv-recognizing,
  title     = {{Recognizing Locations with Google Glass: A Case Study}},
  author    = {Altwaijry, Hani and Moghimi, Mohammad and Belongie, Serge J.},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
  year      = {2014},
  pages     = {167-174},
  doi       = {10.1109/WACV.2014.6836105},
  url       = {https://mlanthology.org/wacv/2014/altwaijry2014wacv-recognizing/}
}