Gist: A Mobile Robotics Application of Context-Based Vision in Outdoor Environment

@article{Siagian2005GistAM,
  title={Gist: A Mobile Robotics Application of Context-Based Vision in Outdoor Environment},
  author={Christian Siagian and Laurent Itti},
  journal={2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops},
  year={2005},
  pages={88-88}
}
We present context-based scene recognition for mobile robotics applications. Our classifier is able to differentiate outdoor scenes without temporal filtering relatively well from a variety of locations at a college campus using a set of features that together capture the "gist" of the scene. We compare the classification accuracy of a set of scenes from 1551 frames filmed outdoors along a path and dividing them to four and twelve different legs while obtaining a classifi- cation rate of 67.96… CONTINUE READING

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