Camera Pose Estimation - Camera characteristics that affect the marker detection
I'am studying the problem of camera pose estimation in particular using ArUco marker and a monocular camera.
The documentations of ArUco and OpenCV are almost perfect, so the problem is not the algorithm itself.
My problem is the camera and its choice.
I need to understand (maybe by a scientific analysis) which camera parameters (eg. focal length, camera aperture, resolution, megapixels, etc.) are most influencing the precision and accuracy of the system, in particular since i have to reach a sub-millimetric accuracy of the detection.
There are many study in which this result is reached (for example this study about a dodecapen), but they use an expensive camera and don't explain the camera features that are more important than others.
So, i can say important camera features for object detection (and pose estimation) are:
- Intrinsic parameters (focal length, principal point, skew etc.) estimated with the calibration
- Lens distortion factors
Moreover, my problem is a detection problem (I've only a photo) and not a tracking problem, even if there are advantages of tracking.
I would like to know for example if the camera of an Ipad is usable for my purposes: I know that there are many augmented reality works (using for example ARKit) on Ipad and Iphone, but what allow me to say that I can use an Ipad to reach a submilllimetric accuracy? ( i know that the response could be "trying the camera in your system"... but i need to prove this thing by a theoretical point of view..).
which parameters do I need to consider to choose the camera?
How can i say (without really use it) that a camera is or is not good?
Do you know any articles, papers or other publications that can help me?
Thanks a lot!
opencv ipad camera augmented-reality aruco
edited Nov 13 at 16:15
Ali Kanat
540216
asked Nov 12 at 14:59
fabridigua
134
add a comment |
I'am studying the problem of camera pose estimation in particular using ArUco marker and a monocular camera.
The documentations of ArUco and OpenCV are almost perfect, so the problem is not the algorithm itself.
My problem is the camera and its choice.
I need to understand (maybe by a scientific analysis) which camera parameters (eg. focal length, camera aperture, resolution, megapixels, etc.) are most influencing the precision and accuracy of the system, in particular since i have to reach a sub-millimetric accuracy of the detection.
There are many study in which this result is reached (for example this study about a dodecapen), but they use an expensive camera and don't explain the camera features that are more important than others.
So, i can say important camera features for object detection (and pose estimation) are:
- Intrinsic parameters (focal length, principal point, skew etc.) estimated with the calibration
- Lens distortion factors
Moreover, my problem is a detection problem (I've only a photo) and not a tracking problem, even if there are advantages of tracking.
I would like to know for example if the camera of an Ipad is usable for my purposes: I know that there are many augmented reality works (using for example ARKit) on Ipad and Iphone, but what allow me to say that I can use an Ipad to reach a submilllimetric accuracy? ( i know that the response could be "trying the camera in your system"... but i need to prove this thing by a theoretical point of view..).
which parameters do I need to consider to choose the camera?
How can i say (without really use it) that a camera is or is not good?
Do you know any articles, papers or other publications that can help me?
Thanks a lot!
opencv ipad camera augmented-reality aruco
edited Nov 13 at 16:15
Ali Kanat
540216
asked Nov 12 at 14:59
fabridigua
134
I am not an expert about opencv but if you are not considering tracking augmented reality solutions are useless for your case. They are already not accurate about tracking and without motion they cant detect objects at all.
– Ali Kanat
Nov 13 at 15:30
add a comment |
I'am studying the problem of camera pose estimation in particular using ArUco marker and a monocular camera.
The documentations of ArUco and OpenCV are almost perfect, so the problem is not the algorithm itself.
My problem is the camera and its choice.
I need to understand (maybe by a scientific analysis) which camera parameters (eg. focal length, camera aperture, resolution, megapixels, etc.) are most influencing the precision and accuracy of the system, in particular since i have to reach a sub-millimetric accuracy of the detection.
There are many study in which this result is reached (for example this study about a dodecapen), but they use an expensive camera and don't explain the camera features that are more important than others.
So, i can say important camera features for object detection (and pose estimation) are:
- Intrinsic parameters (focal length, principal point, skew etc.) estimated with the calibration
- Lens distortion factors
Moreover, my problem is a detection problem (I've only a photo) and not a tracking problem, even if there are advantages of tracking.
I would like to know for example if the camera of an Ipad is usable for my purposes: I know that there are many augmented reality works (using for example ARKit) on Ipad and Iphone, but what allow me to say that I can use an Ipad to reach a submilllimetric accuracy? ( i know that the response could be "trying the camera in your system"... but i need to prove this thing by a theoretical point of view..).
which parameters do I need to consider to choose the camera?
How can i say (without really use it) that a camera is or is not good?
Do you know any articles, papers or other publications that can help me?
Thanks a lot!
opencv ipad camera augmented-reality aruco
edited Nov 13 at 16:15
Ali Kanat
540216
asked Nov 12 at 14:59
fabridigua
134
I'am studying the problem of camera pose estimation in particular using ArUco marker and a monocular camera.
The documentations of ArUco and OpenCV are almost perfect, so the problem is not the algorithm itself.
My problem is the camera and its choice.
I need to understand (maybe by a scientific analysis) which camera parameters (eg. focal length, camera aperture, resolution, megapixels, etc.) are most influencing the precision and accuracy of the system, in particular since i have to reach a sub-millimetric accuracy of the detection.
There are many study in which this result is reached (for example this study about a dodecapen), but they use an expensive camera and don't explain the camera features that are more important than others.
So, i can say important camera features for object detection (and pose estimation) are:
- Intrinsic parameters (focal length, principal point, skew etc.) estimated with the calibration
- Lens distortion factors
Moreover, my problem is a detection problem (I've only a photo) and not a tracking problem, even if there are advantages of tracking.
I would like to know for example if the camera of an Ipad is usable for my purposes: I know that there are many augmented reality works (using for example ARKit) on Ipad and Iphone, but what allow me to say that I can use an Ipad to reach a submilllimetric accuracy? ( i know that the response could be "trying the camera in your system"... but i need to prove this thing by a theoretical point of view..).
which parameters do I need to consider to choose the camera?
How can i say (without really use it) that a camera is or is not good?
Do you know any articles, papers or other publications that can help me?
Thanks a lot!
opencv ipad camera augmented-reality aruco
opencv ipad camera augmented-reality aruco
edited Nov 13 at 16:15
Ali Kanat
540216
asked Nov 12 at 14:59
fabridigua
134
edited Nov 13 at 16:15
Ali Kanat
540216
asked Nov 12 at 14:59
fabridigua
134
edited Nov 13 at 16:15
Ali Kanat
540216
edited Nov 13 at 16:15
Ali Kanat
540216
edited Nov 13 at 16:15
Ali Kanat
540216
540216
asked Nov 12 at 14:59
fabridigua
134
asked Nov 12 at 14:59
fabridigua
134
asked Nov 12 at 14:59
fabridigua
134
134
I am not an expert about opencv but if you are not considering tracking augmented reality solutions are useless for your case. They are already not accurate about tracking and without motion they cant detect objects at all.
– Ali Kanat
Nov 13 at 15:30
add a comment |
I am not an expert about opencv but if you are not considering tracking augmented reality solutions are useless for your case. They are already not accurate about tracking and without motion they cant detect objects at all.
– Ali Kanat
Nov 13 at 15:30
I am not an expert about opencv but if you are not considering tracking augmented reality solutions are useless for your case. They are already not accurate about tracking and without motion they cant detect objects at all.
– Ali Kanat
Nov 13 at 15:30
I am not an expert about opencv but if you are not considering tracking augmented reality solutions are useless for your case. They are already not accurate about tracking and without motion they cant detect objects at all.
– Ali Kanat
Nov 13 at 15:30
add a comment |
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I am not an expert about opencv but if you are not considering tracking augmented reality solutions are useless for your case. They are already not accurate about tracking and without motion they cant detect objects at all.
– Ali Kanat
Nov 13 at 15:30