Context Capture: Acquisition best practices · Data capture requirements and best practices...
Transcript of Context Capture: Acquisition best practices · Data capture requirements and best practices...
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Context Capture: Acquisition best practices
Reality Modeling
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Content
1. Acquisition best practices
2. Drone mapping acquisition rules
3. Indoor acquisition rules
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1 – Acquisition best practices
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Acquisition is the key for a successful processing !
Going from failure …. to success !
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Best Practices for photo acquisition
Context Capture and photo acquisition:
– Photogrammetric principles and limitations
– Camera model and setup
– Data capture requirements & best practices
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Photogrammetric principles
– Based on pixel recognition in multiple photos
– 3 steps process:
• Imagery import
• Aerotriangulation
• Reconstruction
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Processing steps
– Aerotriangulation requirements:
• Good Overlap and scene coverage
• Camera calibration: focal length, Principal Point, distortion parameters
• Pose Metadata: Position (X, Y, Z), Orientation (Ω, Φ, Κ)
– Reconstruction requirements:
• Full coverage of the scene
• Appropriate resolution
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Photogrammetry limitations
– Limitations:
• Moving objects
• Shiny/transparent/reflective surfaces
• Poor texture / no texture surfaces
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Camera model and setup
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Camera model and setup
Hardware:
– Any standard camera (DSLR, Smartphone, bridge, compact, etc.)
– Quality of photo depends of the acquisition device, quality of sensor and optics
Recommendations:
– Keep a constant focal length
– Adjust lighting conditions and camera settings => avoid blurry photos
– Ban geometric retouches
Image format
– High quality JPG, tiff and RAW (RW2, 3FR, DNG, NEF, CRW, CR2)
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Camera model and setup
Shutter speed :
▪ Shutter speed is the most important factor to consider to avoid blurry photos
▪ Easiest parameter to play on
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Camera model and setup
Aperture:
▪ The aperture will affect the amount of light that is captured by the sensor for a given shutterspeed. A small aperture number (f/1.8) means a wide opened diaphragm letting in more light.
▪ The aperture directly affect the depth of field. A bigger aperture number (f/22) means a smallerdiaphragm diameter, letting in less light but with a deeper depth of field, meaning more of thescene in focus.
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Camera model and setup
Camera ISO:
▪ The ISO value represent the sensibility of your sensor. With a high ISO value (high sensibility), yoursensor will need less light for the same pixel brightness. However, a high ISO value will produce morenoise/grain in your photos.
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Data capture requirements and best practices
Overlap:
– Smooth angular and distance transition between photos
– At least 60% overlap between consecutive photos
– 15°maximum angle difference between consecutive photos
– Allows the software to find the link between different sides of an object
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Data capture requirements and best practices
Coverage:
Homogeneous resolution : same distance to objects within a sequence
To capture more details : get closer + add transition photos
Circle around the scene at different level to reveal any masked areas
Always better to capture too many photos than not enough!
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Data capture requirements and best practices
- keep useless information out of the frame: sky, water…
- Necessary to adjust your distance from the subject and/or your optics
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Data capture requirements and best practices
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Real case examples
Ground survey (Bridge)
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Real case examples
Drone 3D mapping (Bentley Systems office)
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Real case examples
City mapping (Marseille)
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Terrestrial scale project
Stage 1: Mission planning
– Is the site accessible?
– What are its rough dimensions?
– What is my exact area of interest?
– What would be the right camera choice?
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Terrestrial scale project
Stage 1: Mission planning
– Site will be accessible from north and free of vehicles
– The site is around 1200sqm and the central part is key
– An estimation of 500-800 images will be required to achieve the mission
– Structure seems high but we should not face backspace issues
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Terrestrial scale project
Stage 2: On-site review
– First global site visit
– Define exact capture path
– Identify potential difficulties
– Determine exact ground control points or scale constraints position
– Camera settings testing
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Terrestrial scale project
Stage 3: Imagery capture
– Follow main capture path and close the loop
– Check primary capture is robust and with no breaks. Images displayed at speed will appear like a movie.
– Focus on key areas: in this instance, the under-part of the bridge
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Terrestrial scale project
Stage 3: Imagery capture
– Before leaving the site, validate the checklist:
• Main capture path is robust
• Focus areas are good and linked to main capture path
• All geo-registration and measurement information has been collected
• Do not forget any materials on-site
– Basic principle reminder:Going back on-site is expensiveIf in doubt, capture additional pictures
Start & Closing
point
Dense capture
on angles
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Terrestrial scale project
Stage 4: Processing
• Copy images to your workstation
• Import images and calibration report
• Define optional positioning constraints: GCPs, scale, etc.
• Submit aerotriangulation to ContextCapture desktop or ContextCapture Cloud Processing Service
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Terrestrial scale project
Stage 4: Processing
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Terrestrial scale project
Stage 5: Mission closure
– Review time spent on:
• Capture
• Automatic processing
• Manual processing
– The importance of planning and preparation stages will be clear
– Reviewing helps accurately define the time and associated costs for planning further missions
Processing stage Processing time
Capture
1- Planification 30min
2- Global tour 10min
3- Image shooting 60min
Processing
1- Manual processing 5min
2- Automatic processing 240min
Summary Project analysis 20min
TOTAL 6h05min
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Processing time
0min
0min
40min
60min
480min
20min
10h00min
Well managed capture Poorly managed capture
Terrestrial scale project
Processing stage Processing time
Capture
1- Planification 30min
2- Global tour 10min
3- Image shooting 60min
Processing
1- Manual processing 5min
2- Automatic processing 240min
Summary Project analysis 20min
TOTAL 6h05min
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2 – Drone mapping acquisition rules
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Drone model
- Fixed wing UAV
- Good autonomy
- Can cover large areas quickly
- Nadir photos only
- Multicopters
- Limited autonomy
- 3D flights allowing for complex flights around assets
- Takes photos from many angles, including upward.
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Drone model:
- Drone selection:
- Acquisition quality depends on drone stability and camera quality
- Recommended to use professional survey drones
- Middle range professional drones:
- Integrated camera
- Average sensor size
- Example: DJI Phantom 4
- High end drones:
- High quality DSLR
- High quality DGNSS positioning
- Example: DJI Matrice and Topcon Falcon 8
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Drone model: Resolution, Precision and Accuracy
Several factors will affect the survey accuracy and precision:
➢ Quality of the capture device
➢ Quality of the photos
➢ Resolution of the photos
➢ Quality of the geo-referencing
➢ Acquisition pattern
➢ Capability of identifying single features in the scene
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Drone model: Resolution, Precision and Accuracy
- Entry price drone and camera
- Georeferencing using GPS tags
- Simple flight pattern (nadir only)
- Quality drone and camera
- Georeferencing using GPS tags
- More complex flight (nadir and obliques)
- Entry price drone and camera
- Georeferencing using ground control points
- Simple flight pattern (nadir only)
- Quality drone and camera
- Georeferencing using ground control points or RTK
- More complex flight (nadir and obliques)
1
2
3
4
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Drone acquisition rules
- Nadir Only:
- Difficult camera calibration. Not suitable for buildings
- Obliques grid:
- Grid pattern
- Better for urban environment
- Overlapping circles:
- Overlapping obliques circles pattern
- Better for buildings and industrial plants
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Drone capture project
Mission purpose
– Produce a reality mesh of Microsoft Redmond site
– Expected accuracy
• Global site: <5cm
– Merge reality mesh with existing lower resolution mesh (larger extents)
– Drone and GCPs approach will be the best choice
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Drone capture project
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Drone capture project
Stage 1: Mission planning from the office
– Define area of take-off and landing and obtain flight clearances
– Identify access to site
– Define drone flight path and GCPs positions for the global area
• Choose the hardware
• Define flight height considering <5cm accuracy expectation
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Drone capture project
Stage 2: On-site review
– Check planned take-off and landing sites
– Check for potential obstacles that could not be foreseen prior to capture
– Set and survey targets for ground control points
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Drone capture project
Stage 3: Imagery capture
– Execute vertical and oblique predefined flight plan
– Fly at constant height
– Avoid flying over the highway
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Drone capture project
Stage 4: Processing
• Copy your images to your workstation
• Import images and ground control points
• Register GCPs
• Submit aerotriangulation to ContextCapture or ContextCapture Cloud Processing Service
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Terrestrial scale project
Stage 5: Mission closure
– Review time spent on:
• Capture
• Automatic processing
• Manual processing
– The importance of planning and preparation stages will be clear
– Reviewing helps accurately define the time and associated costs for planning further missions
Processing stage Processing time
Capture
1- Planification 1h
2- On-site checking 10min
3- Image shooting 8h00min
Processing
1- Manual processing 45min
2- Automatic processing 20days 0h 0min
Summary Project analysis 20min
TOTAL 20d 10h 15min
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Processing time
0min
0min
6h 00min
20h 00min
30d 0h 0min
20min
31d 2h 20min
Well managed capture Poorly managed capture
Drone capture project
Processing stage Processing time
Capture
1- Planification 1h
2- On-site checking 10min
3- Image shooting 8h00min
Processing
1- Manual processing 45min
2- Automatic processing 20d 0h 0min
Summary Project analysis 20min
TOTAL 20d 10h 15min
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Which distance to the objects? Ground Sampling Distance (GSD)
• GSD (ground sampling distance) dependson the camera model, the lens and thedistance from the scene
– R: ground sampling distance
– D : distance to the scene
– f : focal length
– Ls : sensor size
– L : image size in pixel Ls x D / f x L
• R =𝐿𝑠 ∗𝐷
𝑓 ∗𝐿
• Expected precision : P = 2 x R
The calculation of the GSD using this formula is accurate for surfaces that are perpendicular to the line of sight.
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Calculation of the overlap
• Drone flight planning
– Projected image size on the ground: 85 X 63 meters
– Longitudinal overlap: 80 %
– Side overlap: 60%
– Distance between consecutive photos: 63 X 20/100 = 12.6 m
– Distance between two flightlines: 85 X 40/100 = 34 m
Surveys drones are generally provided with flight planning software that handles this calculations.
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Flight planning software
▪ When capturing data with a drone, it is strongly recommended to use a flightplanning application
▪ Some application allows for flight patterns dedicated to Reality Modeling
Example: Drone Harmony (DJI):
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3 – Indoor acquisition rules
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Data capture requirements and best practices
Interior survey: Challenging task!
- Short distance and numerous objects / features creating mask
- Light conditions and windows
- Necessary to increase the number of photos and sequences to increase the overlap: 80%
- Short focal or Fisheye lens is recommended
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Indoor survey - short focal length lens: fisheye
- Non-linear restitution
- Matrix Calibration
- Potential vignetting with bad lighting conditions and average quality lenses
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Indoor survey - short focal length lens: aspheric lenses
- Rectified image with aspheric lens: perspective
- Standard linear calibration
- Potential excessive distortions and low keypoint detection in the corners
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Indoor survey: aperture priority!
• Keep a high depth of field, narrow aperture -> « aperture priority »
- High ISO: advantage with a good quality camera
- The camera will increase the exposure: 1/40, 1/50 can be used for nearby objects and short focus distance
- Aperture wider than f/5.6 -> blurry objects
• Camera testing before the acquisition:
- ISO limit of the camera
- Auto-focus capacity, reduced with wide apertures
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Indoor survey: distance to objects
• Keep a global context
- The algorithm is using surrounding objects for block consolidation
- Transition sequences between areas of interest
- Large sensor size: Keep a high resolution while acquiring a large context
- Changing light condition and windows: monitor images exposure
• ‘Short’ focus distance
- Reduced depth of field
- Potential blurred background
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Indoor survey: acquisition environment
• Changing light
- Low light: avoid using flash, better to use a lighting balloon
- ‘Luminous halo’: avoid reflects, downgraded pixel information around the spots
- White balance: automatic or personalized
• Industrial environment
- Smooth surfaces: use of laser scan, temporary painting
- Add QR codes or April & chilly tags to improve image matching
- Dust: usage of UV filter and regular cleaning
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Interest of QR code for indoor survey
• Time-saving and efficient for
– 3D registration (User Tie-Point)
– Automatic Geo-Referencing (GCP)
– Asset tagging
• Automatic detection in images
• No GPS geo-referencing indoor
• Can be used as tie-point on smooth/evensurfaces QR code generated by ContextCapture
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Use of QR codes in Context Capture
• Generation using dedicated menu
• 3 types:
– User tie point: Robust AT and asset tagging
– Control Point: georeferencing
– Constraint: Origin, scale, axis, plane
• QR code features:
– ‘Quick Response’
– Up to 4300 alphanumeric characters
– Medium redundancy (15% of code can be restored)
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