Leafsnap: A Computer Vision System for Automatic Plant Species Identification

author: Neeraj Kumar, Computer Science and Engineering, Dept. of Computer Science & Engineering, University of Washington
chairman: Michal Irani, Weizmann Institute of Science
chairman: Andrea Vedaldi, Department of Engineering Science, University of Oxford
published: Nov. 12, 2012,   recorded: October 2012,   views: 5910
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

We describe the first mobile app for identifying plant species using automatic visual recognition. The system - called Leafsnap - identifies tree species from photographs of their leaves. Key to this system are computer vision components for discarding non-leaf images, segmenting the leaf from an untextured background, extracting features representing the curvature of the leaf's contour over multiple scales, and identifying the species from a dataset of the 184 trees in the Northeastern United States. Our system obtains state-of-the-art performance on the real-world images from the new Leafsnap Dataset - the largest of its kind. Throughout the paper, we document many of the practical steps needed to produce a computer vision system such as ours, which currently has nearly a million users.

See Also:

Download slides icon Download slides: eccv2012_kumar_vision_01.pdf (2.1┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: