Reality Modeling. Utilizing Drone and Aerial...

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Reality Modeling:Utilising Drone and Aerial Photos November 2017

Presenter: Jerard Marsh

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Quick poll

– ContextCapture users ?

– Other Bentley reality modeling product users ?

– Total beginners ?

– Persons in charge of data capture ?

– Persons consuming reality modeling data ?

Introduction

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What is Reality Modeling ?

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What is reality modeling ?

Capturing existing conditions in 3D using one or a combination devices. (UAVs, Handheld Camera, Laser Scanner)

to support different applications such as

Mapping, Design, Construction, Inspection and Asset Management

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Asset Lifecycle

Why Model Reality?

Identify Need /

Objectives /

Risk

Service /

Performance

Standards Demand /

Load

Forecasts

Funding /

Economic

Modeling

Procurement

Construction

CommissioningOperation

Service

Delivery

Deterioration

and

Maintenance

Condition

Performance

Monitoring

Decomission

Renewal /

Replacement

Understand the

existing conditions

Changes

detection

Risk

management

Document construction

Virtual

Inspection

Visual Operation

Training and

simulation

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Asset Lifecycle

Why Model Reality?

Identify Need /

Objectives /

Risk

Service /

Performance

Standards Demand /

Load

Forecasts

Funding /

Economic

Modeling

Procurement

Understand the

existing conditions

Risk

management

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Asset Lifecycle

Why Model Reality?

Construction

CommissioningOperation

Service

Delivery

Changes

detection

Document construction

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Asset Lifecycle

Why Model Reality?

Deterioration

and

Maintenance

Condition

Performance

Monitoring

Decommission

Renewal /

Replacement

Visual Operation

Training and

simulation

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Asset Lifecycle

Why Model Reality?

Deterioration

and

Maintenance

Condition

Performance

Monitoring

Decommission

Renewal /

Replacement

Virtual

Inspection

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Unlimited Scalability

Why Model Reality?

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Example Aerial Models

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Infrastructure | Petrochemical Plant

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Urban Planning | Aligning Conceptual Design With Reality

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Surveying | Building Conditions and Roof Structures

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Transportation | As-Built Structures Modeling

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Surveying | Stockpile Volume Measurement

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Communication | Illustration of Disaster Impacts

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Mixing aerial and ground

photography

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The interest of the fusion

• Mixing dataset from

different point of view

• Covering the model from

all angles

• Mixing dataset at different

resolution

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Two workflows

• Workflow 1 : mixing dataset that are too different to be matched automatically.

• Workflow 2 : mixing dataset that are difficult to mix fully automatically.

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Two workflows

• Workflow 1 : mixing dataset that are too different to be matched automatically

� Create two independent blocks (or more) : Block_1 / Block_2

� Process AT separately on each of this block.

� Create user tie-points in Block_1 (at least 3). It should be visible in the photos of Block_2 as

well.

� Export the tie-point list in a txt file.

� Import the tie-points as control points in Block_2

� Perform the control points measurement in Block_2

� Resubmit Block_2 AT and choose “use control points for rigid registration”

� Merge both blocks

� Create a reconstruction (adaptive tiling)

� Submit production

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Workflow 1

� Create two independent blocks (or more) : Block_1 / Block_2

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Workflow 1

� Process AT separately on each of this block.

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Workflow 1

� Create user tie-points in Block_1 (at least 3). It should be visible in the photos of Block_2 as well.

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Workflow 1

� Export the tie-point list in a txt file.

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Workflow 1

� Import the tie-points as control points in Block_2

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Workflow 1� Perform the control points measurement in Block_2

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Workflow 1

� Resubmit Block_2 AT and choose “use control points for rigid registration”

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Workflow 1

� Merge both blocks

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Workflow 1

� Create a reconstruction (adaptive tiling)

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Two workflows

• Workflow 2 : mixing dataset that are difficult to mix fully automatically

� Create two independent blocks (or more) : Block_1 / Block_2

� Process AT separately on each of this block.

� Geo-reference both blocks separately (GPS tags, control points, control points extracted

from one block using tie-points).

� Merge both blocks

� Set the block type to “structured aerial dataset”

� Submit a new AT of the merged block

� Create a reconstruction (adaptive tiling)

� Submit production

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Workflow 2

� Create two independent blocks (or more) : Block_1 / Block_2

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Workflow 2

� Geo-reference both blocks separately (GPS tags, control points, control

points extracted from one block using tie-points).

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Workflow 2

� Merge both blocks

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Workflow 2

� Set the block type to “structured aerial dataset”

When a block type is set to structured aerial data and all the photos have position and rotation information,

a tilt ratio is applied to help the keypoint matching of oblique and Nadir photos. Oblique photos will be

shrunk so that the horizontal surfaces will be similar to the nadir photos.

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Workflow 2

� Submit a new AT on the merged block

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Workflow 2

� Create a reconstruction (adaptive tiling)

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Workflow 2

� Submit production

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Demo

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Any questions?

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