Se ha denunciado esta presentación.

Wearable Computer Vision

0

Compartir

Próximo SlideShare
What mean ye storytelling
What mean ye storytelling
Cargando en…3
×
1 de 25
1 de 25

Wearable Computer Vision

0

Compartir

Descargar para leer sin conexión

Intervento di Giovanni Maria Farinella, Professore presso UniCT,
per l'evento "La Computer Vision nell'era dei Big Data"
organizzato da Big Data for You, l'8 novembre 2019.

Intervento di Giovanni Maria Farinella, Professore presso UniCT,
per l'evento "La Computer Vision nell'era dei Big Data"
organizzato da Big Data for You, l'8 novembre 2019.

Más Contenido Relacionado

Libros relacionados

Gratis con una prueba de 30 días de Scribd

Ver todo

Audiolibros relacionados

Gratis con una prueba de 30 días de Scribd

Ver todo

Wearable Computer Vision

  1. 1. Wearable Computer Vision Giovanni Maria Farinella www.dmi.unict.it/farinella gfarinella@dmi.unict.it
  2. 2. Bush’s Memex, 1945 “Certainly progress in photography is not going to stop. […] Let us project this trend ahead to a logical, if not inevitable, outcome. The camera hound of the future wears on his forehead a lump a little larger than a walnut.” https://www.youtube.com/watch?v=c539cK58ees
  3. 3. Wearable Computer Vision: The Goal Clip from movie Terminator 2 - Judgment day: https://youtu.be/9MeaaCwBW28 Ref: https://www.redsharknews.com/vr_and_ar/item/3539-terminator-2-vision-the-augmented-reality-standard-for-25-years
  4. 4. What my research group is doing?
  5. 5. Three Fundamental Tasks of a First Person Vision System WHERE? (localization) WHAT? (understanding) WHAT’S NEXT? (anticipation)
  6. 6. Shopping Cart Localization – Demo https://iplab.dmi.unict.it/EgocentricShoppingCartLocalization/#demo Emiliano Spera, Antonino Furnari, Sebastiano Battiato, Giovanni Maria Farinella (2019). EgoCart: a Benchmark Dataset for Large- Scale Indoor Image-Based Localization in Retail Stores. IEEE Transactions on Circuits and Systems for Video Technology
  7. 7. Dataset Creation – ‘Classic’ Computer Vision! Structure from Motion (SfM) Images 3D Model Attach estimated 6DOF pose to each image camera poses (P,Q) Arbitrary Coordinate System (pose/scale) rotated poses scaled/aligned poses PCA E. Spera, A. Furnari, S. Battiato, G. M. Farinella, Egocentric Shopping Cart Localization, International Conference on Pattern Recognition (ICPR), 2018
  8. 8. Three Fundamental Tasks of a First Person Vision System WHERE? (localization) WHAT? (understanding) WHAT’S NEXT? (anticipation)
  9. 9. VEDI - Vision Exploitation for Data Interpretation Patent Pending – See all Videos Here: https://iplab.dmi.unict.it/VEDI_project/ Where am I? Visitor Site ManagerComputer Vision and Machine Learning • What are the Interesting Sites for the users with Profile A? • User that see X observe also Y • Do we have to re-organize the museum spaces? What objects have been seen by the visitors? How Long? No need of surveys! Clustered Paths - Profile A Clustered Paths - Profile B RI-VEDI Salient Moments See Details! Understanding Visitor Behaviour through Key Performance Indicators and Visual AnaliticsProviding Services Localization Visual Attention Object Recognition Augmented Reality Personal Recommendation Storage/Memories/Summary Behaviour Analysis First Person Vision
  10. 10. The Role of Data
  11. 11. Where and What The VALUE from (Big) Visual Data
  12. 12. https://youtu.be/Cu-pCrLHeZw
  13. 13. Three Fundamental Tasks of a First Person Vision System WHERE? (localization) WHAT? (understanding) WHAT’S NEXT? (anticipation)
  14. 14. Where, What and What’s Next? ? past future Washing Hands
  15. 15. The Role of Data
  16. 16. https://www.youtube.com/watch?v=Dj6Y3H0ubDw&feature=youtu.be
  17. 17. box open turn cut put washtake pan tap pot board food stir pick add pour close bowl bag plate spoon fridge knife rinse get lid onion oil bin still mug fork salt cup mix top flip jar tea bits v60 leaf tin one foil keep tofu skinning fry pin gas tip hot left fan eat cap mat pans dice wait fruit trays make tail bins hit power extra stem lift loafnext snap beer oat mashermustard case tie lay hop emptying rip fix tube bananas dont first cans jeera bar fire tub jars count replace well accessrestart pits kiwis space line rise salsa find flours boat lick done third plain number jugs play stalks app dial swap load wall low air let bun sit dab coke ensure dip wood onoin fla vors co vers whisked waters actual fla t go es redu ce started way do ors big shaking mea surer tonic tasting avoc ad os carrier jasm ine stirrer groc ery scraps forge wan t an gle guide de cide loaves seed save plan ho bs ch ew unzip gallo zero fresh de seed blinds flu ff dials ite m shut snip de spil pico rock drum s mail tilt schedule bite no se prog ram dice d carts realize mats loose runners no w ge ts trying mixed co rd int clam dishing game scourer co nn ec t strip pa ne de pth plated breadcrumbs fuck spin trow stiring grad rim pe n temp cab sole try mess bo w thin pip even fasten pa ce thirty hearts books packs bu g took self puckup leafs sorry po st ice pair large grill stare sort op cu ps four work spate see tun soil 40 Scaling Egocentric Vision Data Collection Native Environment, Natural Interactions Live Narrations Dense Action Segments Active Object Bounding Boxes Benchmark and Challenges 11M Frames 32 kitchens Single-person environments 4 cities May – Nov 2017 – 55 hours 10 nationalities 3 days - all kitchen activities
  18. 18. Annotations Statistics
  19. 19. Annotations Statistics
  20. 20. Annotations – Object Bounding Boxes
  21. 21. Open Challenges 35.13 Object Detection Challenge (34.18) Action Recognition Challenge (63.59) Action Anticipation Challenge (35.13)
  22. 22. RULSTM Antonino Furnari, Giovanni Maria Farinella, What Would You Expect? Anticipating Egocentric Actions with Rolling-Unrolling LSTMs and Modality Attention. International Conference on Computer Vision (ICCV) 2019 - ORAL. Code available at: http://iplab.dmi.unict.it/rulstm/
  23. 23. Demo Video: Egocentric Action Anticipation Antonino Furnari, Giovanni Maria Farinella, What Would You Expect? Anticipating Egocentric Actions with Rolling-Unrolling LSTMs and Modality Attention. International Conference on Computer Vision (ICCV) 2019 - ORAL. Code available at: http://iplab.dmi.unict.it/rulstm/
  24. 24. Thank you for your attention Giovanni Maria Farinella www.dmi.unict.it/farinella gfarinella@dmi.unict.it

×