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Copyright Autoliv Inc., All Rights Reserved Patrik Leissner Feature Developer at Autoliv November 6, 2017 1 Feature Developer at Autoliv

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Copyright Autoliv Inc., All Rights Reserved

Patrik Leissner

Feature Developer at Autoliv

November 6, 20171 Feature Developer at Autoliv

Copyright Autoliv Inc., All Rights ReservedNovember 6, 2017 Feature Developer at Autoliv2

and prevent ten times as many severe injuries

Every year our products save over 30,000 lives

OUR VISION

Saving more lives

0

20000

40000

60000

80000

100000

120000

140000

160000

2015 Target

Goal

Copyright Autoliv Inc., All Rights ReservedNovember 6, 2017 Feature Developer at Autoliv3

Copyright Autoliv Inc., All Rights Reserved

What Can a Camera System Do?

November 6, 2017 Feature Developer at Autoliv4

Lane detection

Traffic sign recognition Light source tracking

Object detection

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Target Tracking

What we want

− Object position (3D)

− Object velocity (2D)

− Object size (height / width / length)

− Object type (car / truck /pedestrian / cyclist / motorcyclist)

What we have

− Output from classifiers

− Optical flow

− Stereo information

− Ego motion

− Camera calibration

November 6, 2017 Feature Developer at Autoliv5

Copyright Autoliv Inc., All Rights Reserved

Detection of Objects

Boosting-based classifiers

Different feature descriptors withincreased complexity

Output given as regions in theimage where objects are detected.

November 6, 2017 Feature Developer at Autoliv6

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Optical Flow

Match pixels in two consecutiveframes (horizontal or vertical)

Pixel motion gives

− Translation

− Scale change

Must take ego motion intoconsideration

November 6, 2017 Feature Developer at Autoliv7

Left

Right

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Stereo Detection

Two cameras

Triangulation gives depthinformation

Segmentation to obtain objectsin the world

November 6, 2017 Feature Developer at Autoliv8

Far

Near

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Stereo Detection – Segmentation

November 6, 2017 Feature Developer at Autoliv9

Copyright Autoliv Inc., All Rights Reserved

Target Tracking – Difficulties

Lots of objects

Dynamics

− Differ between object types

− Generally unknown

− No initial guess

Measurements

− Missing

− False

Initialize tracks

Execution on embedded system

− Real-time requirements

− Resource constraints

November 6, 2017 Feature Developer at Autoliv10

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Movie – Object Detection

November 6, 2017 Feature Developer at Autoliv11

Copyright Autoliv Inc., All Rights Reserved

Reflections of Close Collaboration to Industry

Connection of the work to an actual problem and product.

Hands-on experiments with state of the art technology.

Interesting to test algorithms in reality, not only in simulations.

− However, it is not always possible to test on target hardware

September 19, 2017 Name of presentation12

autoliv.com

Each year, Autoliv’sproducts save over30,000 lives