A complex network-based approach for boundary shape analysis
Pattern Recognition
Automated Flower Classification over a Large Number of Classes
ICVGIP '08 Proceedings of the 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing
Visual-based plant species identification from crowdsourced data
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Multimedia analysis for ecological data
Proceedings of the 20th ACM international conference on Multimedia
Identification of plants from multiple images and botanical IdKeys
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Proceedings of the 21st ACM international conference on Multimedia
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This paper presents a new interactive web application for the visual identification of plants based on collaborative pictures. Contrary to previous content-based identification methods and systems developed for plants that mainly relied on leaves, or in few other cases on flowers, it makes use of five different organs and plant's views including habit, flowers, fruits, leaves and bark. Thanks to an interactive and visual query widget, the tagging process of the different organs and views is as simple as drag-and-drop operations and does not require any expertise in botany. All training pictures used by the system were continuously collected during one year through a crowdsourcing application that was set up in the scope of a citizen sciences initiative. System-oriented and human-centered evaluations of the application show that the results are already satisfactory and therefore very promising in the long term to identify a richer flora.