ZhaoHFUT at ImageCLEF 2012 Plant Identification Task

This paper presents the contribution of ZhaoHFUT group to the ImageCLEF 2012 Plant identification task. The task involves iden- tifying various species of trees based on images of their leaves. In this task, we adopted the main structure of the ScSPM model and another ex- tension of Scale Invariant Feature Transform (SIFT) descriptors, namely flip SIFT descriptors, to investigate the performance of them considering their good performance in object classification. Although our results are not quite promising as compared to other participant groups, they can still guide our work in this field for some conclusions reached.

[1]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[2]  Yihong Gong,et al.  Linear spatial pyramid matching using sparse coding for image classification , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  Cordelia Schmid,et al.  Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[4]  Rajat Raina,et al.  Efficient sparse coding algorithms , 2006, NIPS.

[5]  Yihong Gong,et al.  Linear spatial pyramid matching using sparse coding for image classification , 2009, CVPR.

[6]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.