Detect an Object from long distance using ARKit/CoreMLCan I embed a custom font in an iPhone application?Vision Framework with ARkit and CoreMLIs it possible to get a “SCNVector3” position of a World object using CoreML and ARKit?Detecting object's distance away from camera in augmented reality (ARKit, etc.)?CoreML: iOS: How to get 2D coordinates of center of detected modelHow to measure the dimensions of a 3d object using ARKit or Apple Vision?ARKit Calculate distance from a wall to the cameraObject detection ARKit vs CoreMLHow to access raw features (not just spatial points) ARKit uses to detect objectsWhat are limitations for scanning and detecting 3d object in ARKit2.0 in iOS?
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Detect an Object from long distance using ARKit/CoreML
Can I embed a custom font in an iPhone application?Vision Framework with ARkit and CoreMLIs it possible to get a “SCNVector3” position of a World object using CoreML and ARKit?Detecting object's distance away from camera in augmented reality (ARKit, etc.)?CoreML: iOS: How to get 2D coordinates of center of detected modelHow to measure the dimensions of a 3d object using ARKit or Apple Vision?ARKit Calculate distance from a wall to the cameraObject detection ARKit vs CoreMLHow to access raw features (not just spatial points) ARKit uses to detect objectsWhat are limitations for scanning and detecting 3d object in ARKit2.0 in iOS?
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How can we detect an object from almost any distance using CoreML or ARKit. Currently I have tried ARKIT 3d object scanning and detection which works from the near distance to the object, But as we get far away from the object, it's unable to detect that object. Similarly using CoreML, I have trained a model to detect an object, which was only detecting the object from the near distance. How to achieve object detection from far distances in which actual object obviously gets too small.
ios augmented-reality object-detection arkit coreml
edited Apr 26 at 9:00
ARGeo
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asked Mar 27 at 7:41
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How can we detect an object from almost any distance using CoreML or ARKit. Currently I have tried ARKIT 3d object scanning and detection which works from the near distance to the object, But as we get far away from the object, it's unable to detect that object. Similarly using CoreML, I have trained a model to detect an object, which was only detecting the object from the near distance. How to achieve object detection from far distances in which actual object obviously gets too small.
ios augmented-reality object-detection arkit coreml
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
add a comment |
How can we detect an object from almost any distance using CoreML or ARKit. Currently I have tried ARKIT 3d object scanning and detection which works from the near distance to the object, But as we get far away from the object, it's unable to detect that object. Similarly using CoreML, I have trained a model to detect an object, which was only detecting the object from the near distance. How to achieve object detection from far distances in which actual object obviously gets too small.
ios augmented-reality object-detection arkit coreml
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
How can we detect an object from almost any distance using CoreML or ARKit. Currently I have tried ARKIT 3d object scanning and detection which works from the near distance to the object, But as we get far away from the object, it's unable to detect that object. Similarly using CoreML, I have trained a model to detect an object, which was only detecting the object from the near distance. How to achieve object detection from far distances in which actual object obviously gets too small.
ios augmented-reality object-detection arkit coreml
ios augmented-reality object-detection arkit coreml
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
edited Apr 26 at 9:00
ARGeo
10.6k5 gold badges38 silver badges71 bronze badges
10.6k5 gold badges38 silver badges71 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
asked Mar 27 at 7:41
user2096064user2096064
731 silver badge9 bronze badges
731 silver badge9 bronze badges
add a comment |
add a comment |
1 Answer
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It seems to me that scanning a faraway 3D object has no practical application.
Firstly, you need to scan your object from all available sides in order to recognise that object in the future, not just from one PoV. Secondly, there's sometimes environmental haze (smog, rain) what desaturates such long-distance object and makes it hardly recognisible. And lastly, there's a shortage of details for far-away object's surface, in other words a "texture" is quite poor.
Practical solution for this issue is simple: just use an image recognition technique for pre-taken photo in ARKit and CoreML. And scanned data is much more heavier for iPhone's CPU and GPU than mlmodel, isn't it?
answered Mar 27 at 10:23
ARGeoARGeo
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1 Answer
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It seems to me that scanning a faraway 3D object has no practical application.
Firstly, you need to scan your object from all available sides in order to recognise that object in the future, not just from one PoV. Secondly, there's sometimes environmental haze (smog, rain) what desaturates such long-distance object and makes it hardly recognisible. And lastly, there's a shortage of details for far-away object's surface, in other words a "texture" is quite poor.
Practical solution for this issue is simple: just use an image recognition technique for pre-taken photo in ARKit and CoreML. And scanned data is much more heavier for iPhone's CPU and GPU than mlmodel, isn't it?
answered Mar 27 at 10:23
ARGeoARGeo
10.6k5 gold badges38 silver badges71 bronze badges
add a comment |
It seems to me that scanning a faraway 3D object has no practical application.
Firstly, you need to scan your object from all available sides in order to recognise that object in the future, not just from one PoV. Secondly, there's sometimes environmental haze (smog, rain) what desaturates such long-distance object and makes it hardly recognisible. And lastly, there's a shortage of details for far-away object's surface, in other words a "texture" is quite poor.
Practical solution for this issue is simple: just use an image recognition technique for pre-taken photo in ARKit and CoreML. And scanned data is much more heavier for iPhone's CPU and GPU than mlmodel, isn't it?
answered Mar 27 at 10:23
ARGeoARGeo
10.6k5 gold badges38 silver badges71 bronze badges
add a comment |
It seems to me that scanning a faraway 3D object has no practical application.
Firstly, you need to scan your object from all available sides in order to recognise that object in the future, not just from one PoV. Secondly, there's sometimes environmental haze (smog, rain) what desaturates such long-distance object and makes it hardly recognisible. And lastly, there's a shortage of details for far-away object's surface, in other words a "texture" is quite poor.
Practical solution for this issue is simple: just use an image recognition technique for pre-taken photo in ARKit and CoreML. And scanned data is much more heavier for iPhone's CPU and GPU than mlmodel, isn't it?
answered Mar 27 at 10:23
ARGeoARGeo
10.6k5 gold badges38 silver badges71 bronze badges
It seems to me that scanning a faraway 3D object has no practical application.
Firstly, you need to scan your object from all available sides in order to recognise that object in the future, not just from one PoV. Secondly, there's sometimes environmental haze (smog, rain) what desaturates such long-distance object and makes it hardly recognisible. And lastly, there's a shortage of details for far-away object's surface, in other words a "texture" is quite poor.
Practical solution for this issue is simple: just use an image recognition technique for pre-taken photo in ARKit and CoreML. And scanned data is much more heavier for iPhone's CPU and GPU than mlmodel, isn't it?
answered Mar 27 at 10:23
ARGeoARGeo
10.6k5 gold badges38 silver badges71 bronze badges
edited Mar 27 at 10:32
answered Mar 27 at 10:23
ARGeoARGeo
10.6k5 gold badges38 silver badges71 bronze badges
answered Mar 27 at 10:23
ARGeoARGeo
10.6k5 gold badges38 silver badges71 bronze badges
answered Mar 27 at 10:23
ARGeoARGeo
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10.6k5 gold badges38 silver badges71 bronze badges
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