Transport - Contributions de l’utilisateur [fr]

Equipment

2014-07-08T18:57:38Z

Paul : /* Calibration Matrix */

* 2 tripods
* 1 measuring wheel
* 1 GPS unit with SD card ("Columbus") NS office
* 4 nu-metrics NC-200 traffic sensors: counts, speed and vehicle classification (based on length)
* 1 telescopic pole with surveillance camera encasing that can contain a camera, typically GoPro
* 1 GoPro Hero2 camera with extra wifi module and battery pack + 2 external charger battery (Anker http://www.amazon.ca/gp/product/B009USAJCC?*Version*=1&*entries*=0)
* 1 GoPro Hero3+ white with battery pack
* 1 car (black Ford Escape 2006): parked in the new pavilion (Lassonde); the fob gives us access to the parking of the main pavilion to load up the car through the back door on the 3rd floor, very close to B344

==Rules for the car==

* Register the use of the equipment on the calendar: use the McGill online system http://transpo.herobo.com
* Log all trips with the vehicle: hour you leave and return the vehicle, purpose/destination, km and gas refill
* Fob in and out of the parking every time, even if the barrier is up
* Leave the fob (RFID) hanging on the rear view mirror

==Calibration Matrix==

'''NOTE: Validate these parameters on your data before using them.'''

With GoPro cameras, verify FOV setting. Not all version of the Hero3 support FOV change. Reffer to http://gopro.com/product-comparison-hero3-cameras

Sample parameters for GoPro HD Hero2 1280*960 (In-house calibration), unknown FOV:
camera_matrix = [[377.42, 0.0, 639.12],
[0.0, 378.43, 490.20],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.11759321, 0.0148536, 0.00030756, -0.00020578, -0.00091816]

Sample parameters for GoPro HD Hero3 1280*960 (In-house calibration), "Ultra-Wide" (?) FOV:
camera_matrix = [[568.82, 0.0, 630.27],
[0.0, 565.51, 469.72],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.25889354, 0.0812486 , 0.00119071, 0.0044503 , -0.0119863]

Sample parameters for GoPro HD Hero2 1280*720 http://www.htw-mechlab.de/index.php/undistortion-der-gopro-hd-hero2/:
camera_matrix = [[469.96, 0.0, 640],
[0.0, 467.68, 360],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.18957, 0.037319, 0.0, 0.0, -0.00337]

Sample parameters for GoPro HD Hero2 1920*1080 (In-house calibration), wide FOV:

camera_matrix = [[ 894.18, 0.0, 951.75],
[ 0.0, 913.20, 573.04],
[ 0.0, 0.0, 1.0]]
dist_coeffs = [-0.35887, 0.16375, -0.00081, -0.00074, -0.04039]

Sample parameters for GoPro HD Hero2 4K (In-house calibration):
camera_matrix = [[ 1.80151934e+03, 0.00000000e+00, 1.88663242e+03],
[ 0.00000000e+00, 1.80423487e+03, 1.48375206e+03],
[ 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]]
dist_coeffs = [ -3.41396353e-01, 1.70761088e-01, 1.85596892e-05, 6.56168307e-04, -5.22716120e-02]

Equipment

2014-07-08T18:57:01Z

Paul : /* Calibration Matrix */ Added GoPro HD Hero2 1920*1080 (In-house calibration), wide FOV

* 2 tripods
* 1 measuring wheel
* 1 GPS unit with SD card ("Columbus") NS office
* 4 nu-metrics NC-200 traffic sensors: counts, speed and vehicle classification (based on length)
* 1 telescopic pole with surveillance camera encasing that can contain a camera, typically GoPro
* 1 GoPro Hero2 camera with extra wifi module and battery pack + 2 external charger battery (Anker http://www.amazon.ca/gp/product/B009USAJCC?*Version*=1&*entries*=0)
* 1 GoPro Hero3+ white with battery pack
* 1 car (black Ford Escape 2006): parked in the new pavilion (Lassonde); the fob gives us access to the parking of the main pavilion to load up the car through the back door on the 3rd floor, very close to B344

==Rules for the car==

* Register the use of the equipment on the calendar: use the McGill online system http://transpo.herobo.com
* Log all trips with the vehicle: hour you leave and return the vehicle, purpose/destination, km and gas refill
* Fob in and out of the parking every time, even if the barrier is up
* Leave the fob (RFID) hanging on the rear view mirror

==Calibration Matrix==

'''NOTE: Validate these parameters on your data before using them.'''

With GoPro cameras, verify FOV setting. Not all version of the Hero3 support FOV change. Reffer to http://gopro.com/product-comparison-hero3-cameras

Sample parameters for GoPro HD Hero2 1280*960 (In-house calibration), unknown FOV:
camera_matrix = [[377.42, 0.0, 639.12],
[0.0, 378.43, 490.20],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.11759321, 0.0148536, 0.00030756, -0.00020578, -0.00091816]

Sample parameters for GoPro HD Hero3 1280*960 (In-house calibration), "Ultra-Wide" (?) FOV:
camera_matrix = [[568.82, 0.0, 630.27],
[0.0, 565.51, 469.72],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.25889354, 0.0812486 , 0.00119071, 0.0044503 , -0.0119863]

Sample parameters for GoPro HD Hero2 1280*720 http://www.htw-mechlab.de/index.php/undistortion-der-gopro-hd-hero2/:
camera_matrix = [[469.96, 0.0, 640],
[0.0, 467.68, 360],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.18957, 0.037319, 0.0, 0.0, -0.00337]

Sample parameters for GoPro HD Hero2 1920*1080 (In-house calibration), wide FOV:

camera_matrix = [[ 894.18, 0.0, 951.75],
[ 0.0, 913.20, 573.04],
[ 0.0, 0.0, 1.0]]

dist_coeffs = [[-0.35887, 0.16375, -0.00081, -0.00074, -0.04039]]

Sample parameters for GoPro HD Hero2 4K (In-house calibration):
camera_matrix = [[ 1.80151934e+03, 0.00000000e+00, 1.88663242e+03],
[ 0.00000000e+00, 1.80423487e+03, 1.48375206e+03],
[ 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]]
dist_coeffs = [ -3.41396353e-01, 1.70761088e-01, 1.85596892e-05, 6.56168307e-04, -5.22716120e-02]

Equipment

2014-06-10T17:57:35Z

Paul : /* Calibration Matrix */

* 2 tripods
* 1 measuring wheel
* 1 GPS unit with SD card ("Columbus") NS office
* 4 nu-metrics NC-200 traffic sensors: counts, speed and vehicle classification (based on length)
* 1 telescopic pole with surveillance camera encasing that can contain a camera, typically GoPro
* 1 GoPro Hero2 camera with extra wifi module and battery pack + 2 external charger battery (Anker http://www.amazon.ca/gp/product/B009USAJCC?*Version*=1&*entries*=0)
* 1 GoPro Hero3+ white with battery pack
* 1 car (black Ford Escape 2006): parked in the new pavilion (Lassonde); the fob gives us access to the parking of the main pavilion to load up the car through the back door on the 3rd floor, very close to B344

==Rules for the car==

* Register the use of the equipment on the calendar: use the McGill online system http://transpo.herobo.com
* Log all trips with the vehicle: hour you leave and return the vehicle, purpose/destination, km and gas refill
* Fob in and out of the parking every time, even if the barrier is up
* Leave the fob (RFID) hanging on the rear view mirror

==Calibration Matrix==

'''NOTE: Validate these parameters on your data before using them.'''

With GoPro cameras, verify FOV setting. Not all version of the Hero3 support FOV change. Reffer to http://gopro.com/product-comparison-hero3-cameras

Sample parameters for GoPro HD Hero2 1280*960 (In-house calibration), unknown FOV:
camera_matrix = [[377.42, 0.0, 639.12],
[0.0, 378.43, 490.20],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.11759321, 0.0148536, 0.00030756, -0.00020578, -0.00091816]

Sample parameters for GoPro HD Hero3 1280*960 (In-house calibration), "Ultra-Wide" (?) FOV:
camera_matrix = [[568.82, 0.0, 630.27],
[0.0, 565.51, 469.72],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.25889354, 0.0812486 , 0.00119071, 0.0044503 , -0.0119863]

Sample parameters for GoPro HD Hero2 1280*720 http://www.htw-mechlab.de/index.php/undistortion-der-gopro-hd-hero2/:
camera_matrix = [[469.96, 0.0, 640],
[0.0, 467.68, 360],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.18957, 0.037319, 0.0, 0.0, -0.00337]

Sample parameters for GoPro HD Hero2 4K (In-house calibration):
camera_matrix = [[ 1.80151934e+03, 0.00000000e+00, 1.88663242e+03],
[ 0.00000000e+00, 1.80423487e+03, 1.48375206e+03],
[ 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]]
dist_coeffs = [ -3.41396353e-01, 1.70761088e-01, 1.85596892e-05, 6.56168307e-04, -5.22716120e-02]

Equipment

2014-06-10T17:50:08Z

Paul : /* Calibration Matrix */

* 2 tripods
* 1 measuring wheel
* 1 GPS unit with SD card ("Columbus") NS office
* 4 nu-metrics NC-200 traffic sensors: counts, speed and vehicle classification (based on length)
* 1 telescopic pole with surveillance camera encasing that can contain a camera, typically GoPro
* 1 GoPro Hero2 camera with extra wifi module and battery pack + 2 external charger battery (Anker http://www.amazon.ca/gp/product/B009USAJCC?*Version*=1&*entries*=0)
* 1 GoPro Hero3+ white with battery pack
* 1 car (black Ford Escape 2006): parked in the new pavilion (Lassonde); the fob gives us access to the parking of the main pavilion to load up the car through the back door on the 3rd floor, very close to B344

==Rules for the car==

* Register the use of the equipment on the calendar: use the McGill online system http://transpo.herobo.com
* Log all trips with the vehicle: hour you leave and return the vehicle, purpose/destination, km and gas refill
* Fob in and out of the parking every time, even if the barrier is up
* Leave the fob (RFID) hanging on the rear view mirror

==Calibration Matrix==

'''NOTE: Validate these parameters on your data before using them.'''

Sample parameters for GoPro HD Hero2 1280*960 (In-house calibration), unknown FOV:
camera_matrix = [[377.42, 0.0, 639.12],
[0.0, 378.43, 490.20],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.11759321, 0.0148536, 0.00030756, -0.00020578, -0.00091816]

Sample parameters for GoPro HD Hero3 1280*960 (In-house calibration), unknown FOV:
camera_matrix = [[568.82, 0.0, 630.27],
[0.0, 565.51, 469.72],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.25889354, 0.0812486 , 0.00119071, 0.0044503 , -0.0119863]

Sample parameters for GoPro HD Hero2 1280*720 [Source](http://www.htw-mechlab.de/index.php/undistortion-der-gopro-hd-hero2/):
camera_matrix = [[469.96, 0.0, 640],
[0.0, 467.68, 360],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.18957, 0.037319, 0.0, 0.0, -0.00337]

Sample parameters for GoPro HD Hero2 4K (In-house calibration):
camera_matrix = [[ 1.80151934e+03, 0.00000000e+00, 1.88663242e+03],
[ 0.00000000e+00, 1.80423487e+03, 1.48375206e+03],
[ 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]]
dist_coeffs = [ -3.41396353e-01, 1.70761088e-01, 1.85596892e-05, 6.56168307e-04, -5.22716120e-02]

Equipment

2014-06-05T20:49:45Z

Paul : Calibration parameters

* 2 tripods
* 1 measuring wheel
* 1 GPS unit with SD card ("Columbus") NS office
* 4 nu-metrics NC-200 traffic sensors: counts, speed and vehicle classification (based on length)
* 1 telescopic pole with surveillance camera encasing that can contain a camera, typically GoPro
* 1 GoPro Hero2 camera with extra wifi module and battery pack + 2 external charger battery (Anker http://www.amazon.ca/gp/product/B009USAJCC?*Version*=1&*entries*=0)
* 1 GoPro Hero3+ white with battery pack
* 1 car (black Ford Escape 2006): parked in the new pavilion (Lassonde); the fob gives us access to the parking of the main pavilion to load up the car through the back door on the 3rd floor, very close to B344

==Rules for the car==

* Register the use of the equipment on the calendar: use the McGill online system http://transpo.herobo.com
* Log all trips with the vehicle: hour you leave and return the vehicle, purpose/destination, km and gas refill
* Fob in and out of the parking every time, even if the barrier is up
* Leave the fob (RFID) hanging on the rear view mirror

==Calibration Matrix==

'''NOTE: Validate these parameters on your data before using them.'''

Sample parameters for GoPro HD Hero2 1280*960 (In-house calibration):
camera_matrix = [[377.42, 0.0, 639.12],
[0.0, 378.43, 490.20],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.11759321, 0.0148536, 0.00030756, -0.00020578, -0.00091816]

Sample parameters for GoPro HD Hero2 1280*720 [Source](http://www.htw-mechlab.de/index.php/undistortion-der-gopro-hd-hero2/):
camera_matrix = [[469.96, 0.0, 640],
[0.0, 467.68, 360],
[0.0, 0.0, 1.0]]
dist_coeffs = [-0.18957, 0.037319, 0.0, 0.0, -0.00337]

Sample parameters for GoPro HD Hero2 4K (In-house calibration):
camera_matrix = [[ 1.80151934e+03, 0.00000000e+00, 1.88663242e+03],
[ 0.00000000e+00, 1.80423487e+03, 1.48375206e+03],
[ 0.00000000e+00, 0.00000000e+00, 1.00000000e+00]]
dist_coeffs = [ -3.41396353e-01, 1.70761088e-01, 1.85596892e-05, 6.56168307e-04, -5.22716120e-02]