Fcv appli science_perona

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Technology Education

Applications to Science

Pietro Perona
California Institute of Technology

NSF Workshop - Frontiers in Vision
Cambridge, 23 Aug 2011

Friday, August 26, 2011

Goals

• A few examples
• Implications for machine vision
• Lessons learned
• NSF’s role

Friday, August 26, 2011

Plan

• Intro (5’)
• Sketch of a few success stories (50’)
• Discussion (10’)

Friday, August 26, 2011

‘Lunging’ (view from top)

Friday, August 26, 2011

Why measure behavior

Friday, August 26, 2011

Why measure behavior

• Genes <<>> Brains <<>> Behavior

Friday, August 26, 2011

Why measure behavior

• Genes <<>> Brains <<>> Behavior
• Ethology

Friday, August 26, 2011

Why measure behavior

• Genes <<>> Brains <<>> Behavior
• Ethology
• What is behavior?

Friday, August 26, 2011

Fly behavior
(as we understand it today)

Adapted from:
Kravitz et al.
PNAS April 16, 2002
vol. 99 no. 8
5664–5668

Friday, August 26, 2011

Detection performance

[Dankert et al., Nature Methods, April 2009]
Friday, August 26, 2011

Phenotyping

[Dankert et al., Nature Methods, 2009]
Friday, August 26, 2011

Ethograms

[Dankert et al., Nature Methods, April 2009]
Friday, August 26, 2011

Perception

PSYCHOLOGY
interaction, cooperation,
competition

plans, goals, behavior,
relationships ...

pose, movemes, actions,
activities, objects, scenes

SENSORY
images, trajectories

World
Friday, August 26, 2011

Action Perception

PSYCHOLOGY
interaction, cooperation,
PLANNING
group-level goals and plans
competition
SOCIAL NETWORK THEORY OF SOCIOLOGY
INDIVIDUAL

plans, goals, behavior,
individual goals and plans
relationships ...
PREFRONTAL CORTEX THEORY OF PSYCHOLOGY

pose, movemes, actions,
MOTOR

motor programs
activities, objects, scenes

SENSORY
MOTOR CORTEX RECOGNITION

sensor-based control images, trajectories
SPINAL CORD IMAGING,TRACKING

World
Friday, August 26, 2011

Lessons learned
• Image deluge in science
• Doing better than the scientists
• Payoffs in science, not in MV (short term)
‣ Must work as scientist
‣ Students must be interested in science too
‣ Publish in unfamiliar venues
‣ CV publications are suspicious

• Beneﬁt to MV: new challenges and datasets
• Beneﬁt to PI: fun, learning
Friday, August 26, 2011

Basic research needed

• Tracking, detection and identiﬁcation
• Parts and pose
• Hierarchical models (for time series)
• Unsupervised discovery of categories
• Weakly supervised learning

Friday, August 26, 2011

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Fcv appli science_perona

1. Applications to Science Pietro Perona California Institute of Technology NSF Workshop - Frontiers in Vision Cambridge, 23 Aug 2011 Friday, August 26, 2011

2. Goals • A few examples • Implications for machine vision • Lessons learned • NSF’s role Friday, August 26, 2011

3. Plan • Intro (5’) • Sketch of a few success stories (50’) • Discussion (10’) Friday, August 26, 2011

4. ‘Lunging’ (view from top) Friday, August 26, 2011

5. Why measure behavior Friday, August 26, 2011

6. Why measure behavior • Genes <<>> Brains <<>> Behavior Friday, August 26, 2011

7. Why measure behavior • Genes <<>> Brains <<>> Behavior • Ethology Friday, August 26, 2011

8. Why measure behavior • Genes <<>> Brains <<>> Behavior • Ethology • What is behavior? Friday, August 26, 2011

9. Fly behavior (as we understand it today) Adapted from: Kravitz et al. PNAS April 16, 2002 vol. 99 no. 8 5664–5668 Friday, August 26, 2011

10. Friday, August 26, 2011

11. Friday, August 26, 2011

12. Detection performance [Dankert et al., Nature Methods, April 2009] Friday, August 26, 2011

13. Phenotyping [Dankert et al., Nature Methods, 2009] Friday, August 26, 2011

14. Ethograms [Dankert et al., Nature Methods, April 2009] Friday, August 26, 2011

15. Perception PSYCHOLOGY interaction, cooperation, competition plans, goals, behavior, relationships ... pose, movemes, actions, activities, objects, scenes SENSORY images, trajectories World Friday, August 26, 2011

16. Action Perception PSYCHOLOGY interaction, cooperation, PLANNING group-level goals and plans competition SOCIAL NETWORK THEORY OF SOCIOLOGY INDIVIDUAL plans, goals, behavior, individual goals and plans relationships ... PREFRONTAL CORTEX THEORY OF PSYCHOLOGY pose, movemes, actions, MOTOR motor programs activities, objects, scenes SENSORY MOTOR CORTEX RECOGNITION sensor-based control images, trajectories SPINAL CORD IMAGING,TRACKING World Friday, August 26, 2011

17. Lessons learned • Image deluge in science • Doing better than the scientists • Payoffs in science, not in MV (short term) ‣ Must work as scientist ‣ Students must be interested in science too ‣ Publish in unfamiliar venues ‣ CV publications are suspicious • Beneﬁt to MV: new challenges and datasets • Beneﬁt to PI: fun, learning Friday, August 26, 2011

18. Basic research needed • Tracking, detection and identiﬁcation • Parts and pose • Hierarchical models (for time series) • Unsupervised discovery of categories • Weakly supervised learning Friday, August 26, 2011

Fcv appli science_perona

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