Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond keypoints: novel techniques for content-based image matching and retrieval
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
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Local feature based methods have achieved a great success in the field of image matching due to its invariance under typical image transformations. However, local features are often not invariant under complex nonaffine transformations, which makes the matching methods ineffective. To remove the effect of complex image transformations, this paper proposes alignment of images before they are compared. An automatic image alignment method is introduced based on thin plate spline (TPS) warping. Then, the aligned matching scheme is designed to utilize correct alignments and reject false alignments for the improvement of matching performance. The method is evaluated using scene retrieval and object categorization. Experiments show the proposed aligned matching outperforms two typical methods: voting scheme and histograms comparison (over a set of prototypes which must be found by clustering).