This paper propose to make the matching directly in the frequency domain and is the predecessor of LPM. It also discuss using the Periodic FFT instead of the FFT as well as a trick to improve the consensus check.
- Robust and Invariant Phase Based Local Feature Matching. A. Hast. ICPR 2014, Poster with paper. pp. 809-814. 2014.
@inproceedings{Has14a, author = {A. Hast}, title = {Robust and Invariant Phase Based Local Feature Matching}, booktitle = {ICPR 2014}, pages = {809--814}, note = {Poster with Paper}, year = {2014}}
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Anders Hast received a PhD in Computerised Image processing at Uppsala university in 2004. In 2011 he spent one year at IIT, CNR, Pisa in Italy as an ERCIM fellow and after that he received a full time position as associate professor and in 2019 he became professor in image processing, both at Uppsala University. He has been affiliated with UPPMAX super computer centre where he worked as an application expert in Scientific Visualisation and later in the field of digital humanities together with the Centre for digital humanities in Uppsala. His recent research has focused on image processing and computer vision, for applications in microscopy, aerial photography, object recognition and especially hand written text recognition and face recognition.
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Anders Hast 