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https://github.com/curvsurf/findsurface-guidemo-ios
The demo app demonstrates a real-time application using FindSurface to search point clouds, which ARKit provides, for geometry shapes.
https://github.com/curvsurf/findsurface-guidemo-ios
ios swift
Last synced: about 2 months ago
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The demo app demonstrates a real-time application using FindSurface to search point clouds, which ARKit provides, for geometry shapes.
- Host: GitHub
- URL: https://github.com/curvsurf/findsurface-guidemo-ios
- Owner: CurvSurf
- License: mit
- Created: 2021-09-17T08:56:37.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-10-29T06:57:56.000Z (2 months ago)
- Last Synced: 2024-10-29T07:30:56.036Z (2 months ago)
- Topics: ios, swift
- Language: Swift
- Homepage:
- Size: 29.1 MB
- Stars: 10
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE
Awesome Lists containing this project
README
# FindSurface-GUIDemo-iOS (Swift)
**Curv*Surf* FindSurface™** GUIDemo for iOS (Swift)
## Overview
This demo app demonstrates a real-time application using FindSurface to search point clouds, which ARKit provides, for geometry shapes.
**NOTE:** The repositories listed below are presently inaccessible due to internal complications. If you have any inquiries or require further assistance in relation to this matter, please contact to [email protected]. We greatly appreciate your patience and understanding during this period.
[FindSurfaceFramework](https://github.com/CurvSurf/FindSurface-iOS) is required to build the source code into a program. Download the framework [here](https://github.com/CurvSurf/FindSurface-iOS/releases) and refer to [here](https://github.com/CurvSurf/FindSurface-iOS/blob/master/How-to-import-FindSurface-Framework-to-your-project.md) for an instruction about how to setup your project to build it with the framework.
## Requirements
This demo app requires the LiDAR sensor to get a point cloud from ARKit.
- Apple iPad Pro LiDAR
- Apple iPhone 12 Pro
- Apple iPhone 12 Pro Max
- Apple iPhone 13 Pro
- Apple iPhone 13 Pro Max
## Features
Compared to the [basic demo](https://github.com/CurvSurf/FindSurface-BasicDemo-iOS), the gui demo has the following features:
- Real-time detection of surfaces in camera scenes;
- Using input point cloud data provided by ARKit;
- Detected surfaces rendered in overlay (AR rendering);
- GUI interfaces to manipulate the app's settings (e.g., confidence, smoothed depth, feature types).
## User Interface
1. [Feature types](https://github.com/CurvSurf/FindSurface#auto-detection) of surfaces to detect.
2. Hide/show the point cloud on the screen.
3. Confidence levels to filter point cloud (e.g., the "`C.Med`" option means filter out the points having "low" confidence).
4. Point cloud scanning mode.
- "Fixed(`Fix`)" means that FindSurface takes about 20k points from ARKit as an input for each frame.
- "Accumulate(`Acc`)" means it takes about 500 points from ARKit as an input for each frame and accumulates them into a 500k points-sized buffer in a FIFO manner. The points are not accumulated unless the camera has a movement.
5. Switch between smoothed scene depths and scene depths (ARKit option).
6. Accuracy (error) levels of the target surface.
7. Enable/disable FindSurface to start searching geometric shapes.
8. Undo the latest snapshot.
9. Remove all snapshots.
10. Radius indicators.
- The [seed radius](https://github.com/CurvSurf/FindSurface#how-does-it-work) indicator (the white circle), controlled by pinching the screen.
- The picking radius indicator (the red circle), controlled by dragging the screen vertically.
- The focusing point (the blue box) indicates the aim to the target object, to choose a [seed point](https://github.com/CurvSurf/FindSurface#how-does-it-work).
11. (A) Target surface information.
12. (B) Third-person perspective view mode (experimental, see the snapshot in the [Output Examples](#output-examples))
13. Points shown on the screen are the visualization of the points provided by ARKit, of which colors indicate confidence levels (green, blue, and red mean high, medium, and low, respectively).
## About Noise Level Estimation
`FindSurface` requires *a priori* root-mean-squared error of the measurement points (See the measurement accuracy description in [this document](https://github.com/CurvSurf/FindSurface#how-does-it-work) for details). To determine an appropriate value of the measurement accuracy parameter, we built a linear model of normal noise for the app:
````
base_error(distance) = a + b * distance * 2
// the distance is in meters.
````
We set the values of `a = 0.001` and `b = 0.00005` for the normal (expected) noise model as a result of our experiments and introduced an additional constant values for each model, of which the values have been heuristically determined, to derive the following variations of the model:
````
lower_error(distance) = base_error(distance) - 0.001
normal_error(distance) = base_error(distance) + 0.001
higher_error(distance) = base_error(distance) + 0.003
````
The app calculates a concrete value of the *a priori* error according to the distance and the error level that users set (e.i., `E.Low`, `E.Med`, and `E.High`).
## Output Examples
**A sphere is detected**
**Points are hidden**
**Accumulated points**
**Third-person perspective view**
