SIFT Flow: Dense Correspondence across Scenes and Its Applications

  title={SIFT Flow: Dense Correspondence across Scenes and Its Applications},
  author={Ce Liu and Jenny Yuen and Antonio Torralba},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
While image alignment has been studied in different areas of computer vision for decades, aligning images depicting different scenes remains a challenging problem. Analogous to optical flow, where an image is aligned to its temporally adjacent frame, we propose SIFT flow, a method to align an image to its nearest neighbors in a large image corpus containing a variety of scenes. The SIFT flow algorithm consists of matching densely sampled, pixelwise SIFT features between two images while… CONTINUE READING
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