ACM SIGGRAPH 2004 Papers
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
A Visual Vocabulary for Flower Classification
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Automated Flower Classification over a Large Number of Classes
ICVGIP '08 Proceedings of the 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing
Efficient Additive Kernels via Explicit Feature Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pairwise rotation invariant co-occurrence local binary pattern
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
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In this work, we introduce a rapid and accurate flower/leaf recognition system. The system could process one query in less than 0.35s with users' simple interaction. Meanwhile, high accuracy and recall is achieved. Furthermore, low computational resource and memory cost are required by the system. Now, the system is demonstrated on 172 categories of flowers, the largest flower dataset until now, and 220 categories of leaves.