Art of the Tech

Future with Machine Vision

Nazli Temur

Computer Vision Engineer @ ATP

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Outline

Computer Vision Introduction

Teaching Machines Human Perceived World.

Challenges of Visual Perception

Computer Vision through Deep Learning

Conclusion

Demo

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Computer Vision IntroductionVision

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“Computer Vision” is about

extracting semantic information

through visual perceptions.

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Domain Examples

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How did we come here

Orthographic Projection

Perspective Projection

Photography

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Where we are..

Stereo Projection(Epipolar)

Fisheye Projection

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Where we go through

We run after an enhanced way of

capturing the visual information

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Human Machine Interaction

Teaching machines humans’

visual world.

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Judgements Perceptions+ = Thinking

can explain the past ,

understand the present,

estimate the future

Cause and Effect

[Activities/Happenings] [Visual Information]

Visual Perceptions

-detection/tracking/recognition

Video Activity Recognition

?

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It is quoted by Professor David Derkins from Harvard University: ‘’up to 90% of errors in thinking are in perception not judgement’’.

When visual information is perceived or processed incorrectly, it cannot be matched or integrated with our other

senses.

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For a machine which is capable

of thinking like a human, the

ultimate need is ;

Because it combines our visual perception

with our judgements.

“Video Activity Recognition”

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So, for a machine what is “activity recognition” about?

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Activity Recognition

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Activity Recognition

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For machine easiest way to achieve “activity recognition” is copying

cognitive subprocess underlying our visual perception and judgements

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Artificial Intelligence

Computer Vision through Deep

Learning

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What is Deep Learning?

Deep Learning is a subfield of machine learning concerned with

algorithms inspired by the structure and function of the brain called

artificial neural networks.

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Deep Learning Examples on Art

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Is the deep learning complete ?

The knowledge about physical properties of the objects can not be gained by perception…

[Kant]

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Deep Learning Examples on Art

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So, what do we expect from deep learning (AI) ?

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or by This!

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or by This!

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Available Deep Learning

Frameworks - ToolsSoftware Development

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caffe

theano

torch

tensorflow

mxnet

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Challenges - Visual PerceptionComputer Vision

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Calibration

We need to ensure that everybody sees

straight line straight and curvature as curve.

An example with honeybee on mobile robots is here

https://www.ncbi.nlm.nih.gov/pubmed/12009050

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Occlusions

Perspective effect

Noise

Detection Challenges

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Re-identification

Noise

Real-time Processing

Tracking Challenges

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Activity Recognition Challenges

Human is a complex & complicated.

Activities are compositional.

Environment is unconstrained.

Context impact the level of detail.

Realtime happenings require high computation

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Futurism

Concluding with Brave New

Future with Machine Vision

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Heraclitus said ‘’expect the unexpected’’http://www.mirror.co.uk/news/uk-news/killer-robots-use-facial-recognition-11557764

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Conclusion

•Machines are getting smarter, mobile and intractable

•We create them to involve our lives , so they will be following our rules.

•If only we design them according to human visual perception and judgements.

• Deep Learning is in-directly associated with human judgement.

•Deep learning can help us better defining activities and knowing about human s

•For a better future we need to convince Computer Scientists and AI Geeks :D

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Audience

Poll LinkReset

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Thank you!Questions?Questions?

Twitter: @DahaNlr

Gmail: temur.nazli@gmail.com

Linkedin: https://www.linkedin.com/in/nazlitemur/

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