Chad Voegele Selective Search for Object Recognition Outline 1. - - PowerPoint PPT Presentation

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Chad Voegele Selective Search for Object Recognition Outline 1. - - PowerPoint PPT Presentation

Dec 01, 2023 340 likes •776 views

Chad Voegele Selective Search for Object Recognition Outline 1. Individual contribution of region similarity measures 2. Importance of good base segmentation 3. Box overlap correspondence to recognition 3 Outline 1. Individual contribution

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Chad Voegele

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Selective Search for Object Recognition

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Outline

  • 1. Individual contribution of region similarity measures
  • 2. Importance of good base segmentation
  • 3. Box overlap correspondence to recognition

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Outline

  • 1. Individual contribution of region similarity measures
  • 2. Importance of good base segmentation
  • 3. Box overlap correspondence to recognition

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Similarity Measures

Color Texture Size Fill

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Color Similarity

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Color Similarity

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Color Similarity

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Color Similarity

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Texture Similarity

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Texture Similarity

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Texture Similarity

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Texture Similarity

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Size Similarity

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Size Similarity

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Size Similarity

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Size Similarity

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Fill Similarity

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Fill Similarity

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Fill Similarity

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Outline

  • 1. Individual contribution of region similarity measures
  • 2. Importance of good base segmentation
  • 3. Box overlap correspondence to recognition

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Success Case

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Success Case

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Failure Cases

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Failure Cases

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Failure Cases

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Failure Cases

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Outline

  • 1. Individual contribution of region similarity measures
  • 2. Importance of good base segmentation
  • 3. Box overlap correspondence to recognition

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Box Overlaps

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Box Overlaps

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1.

  • strich

2. Arabian camel 3. black stork 4. llama 1. zebra 2. tiger 3. triceratops 4. tiger cat 1. chime, gong 2. plate rack 3. snake fence 4.

  • rgan
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Box Overlaps

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Score: 0.85 1.

  • strich

2. black stork 3. vulture 4. Arabian camel Score: 0.95 1. chime, gong 2. snake fence 3.

  • rgan

4. thatched roof Score: 0.89 1. zebra 2. tiger 3. trcieratops 4. tiger cat

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Box Overlaps

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Score: 0.50 1. zebra 2. tiger 3. gazelle 4. impala Score: 0.50 1.

  • strich

2. llama 3. Arabian camel 4. vulture Score: 0.50 1. snake fence 2. plate rack 3. bannister 4. picket fence

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Box Overlaps

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Score: 0.51 1. zebra 2. fire screen 3. gazelle 4. patas (monkey) Score: 0.50 1. borzoi (dog) 2. timber wolf 3. red wolf 4. badger Score: 0.50 1. plate rack 2. chime, gong 3. shoji (Japanese door) 4. window shade

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Issues

  • Author released half p-code, half m-code.
  • Optimal segmentation coloring problem.
  • AlexNet output very sensitive to image patch size.

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Sources

Code

  • http://koen.me/research/selectivesearch/
  • http://caffe.berkeleyvision.org/

Pictures

  • PASCAL Visual Object Class Challenge 2007: http://host.robots.ox.ac.uk/pascal/VOC/voc2007/index.html
  • http://artisanhardware.com/wp-content/uploads/2015/09/47c6ebf4-7a3e-4345-acb5-6a23c9b0b405.jpg
  • https://upload.wikimedia.org/wikipedia/en/9/93/Pacersoriginallogo.gif
  • http://animaliaz-life.com/data_images/koala/koala4.jpg
  • http://www.synlawngolf.com/wp-content/gallery/golf-installations/golf-027.jpg
  • https://indierevolver.files.wordpress.com/2015/07/chewbacca-han-solo-e1436634523782.jpg
  • http://cdn0.sbnation.com/imported_assets/196372/200803231600576549171-p2.jpeg
  • http://www.planetizen.com/files/images/ChicagoEl.jpg
  • https://www.flickr.com/photos/128888346@N02/24927420741
  • https://upload.wikimedia.org/wikipedia/commons/5/52/Madrid_Zoo.jpg

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Appendix

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Initial Segmentations

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Initial Segmentations

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Initial Segmentations

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Initial Segmentations

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Box Overlap

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1.

  • xcart

2.

  • x

3. horse cart 4. zebra 5. llama 6. bighorn sheep 7. ram 8. water buffalo 9. warthog 10. dogsled