lazy photographer

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Lazy Photographer. 林士涵. 林士涵. 林士涵. 林士涵. 林士涵. 林士涵. 林士涵. 林士涵. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 黃彥翔. 張嫚家. 張嫚家. 張嫚家. 張嫚家. 張嫚家. 張嫚家. 張嫚家. 張嫚家. 張嫚家. 張嫚家. Motivation. ‧ A lazy photographer - PowerPoint PPT Presentation

TRANSCRIPT

  • Lazy Photographer

  • Motivation A lazy photographer after traveling, we want to see photos as soon as possible.

  • Four approaches remove over exposure remove blur image remove (denote) duplication clustering the photos by scene

  • Over exposure use Lab color space split photo to blocks use L value and the distance ab to (0,0) set various thresholds to detect Correcting Over-Exposure in Photographs (must read)

  • Blur deal with vibration or defocused Use gradient magnitude + gradient direction as a feature vector take 100 blur photos and 100 non-blur to train a model by SVM Blurred Image Detection and Classification (must read)

  • Duplication compare photo with SIFT feature compare with the next n photos

  • Clustering based on SIFT feature union similar photos set thresholds to detect

  • Result dataset : 120 photos with 23 over exposure 43 blur photos dataset2 : 60 photos in a single trip

  • DEMO TIME

  • Result (cont.) Blur detection Recall 83.72% (36/43) Precision 76.60% (36/47) Over exposure Recall 82.60% (19/23) Precision 79.17% (19/24)

  • Conclusion & future Auto photo adjustment based on our system, fast and convenient replace or correct over exposure parts deblur user-friendly UI

  • Thank you!