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alamboleyalamboley
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added some GUI
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‎Assets/Prefabs.meta‎

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‎Assets/Prefabs/GestureOnScreen.prefab‎

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‎Assets/Prefabs/GestureOnScreen.prefab.meta‎

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Assets/Scene/Test.unity renamed to Assets/Scene/Demo.unity

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Assets/Scene/Test.unity.meta renamed to Assets/Scene/Demo.unity.meta

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‎Assets/Scripts/CapturePoints.cs‎

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public class CapturePoints : MonoBehaviour {
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public Transform gestureOnScreen;
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public Transform gestureOnScreenPrefab;
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private List<Gesture> trainingSet = new List<Gesture>();
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private List<Point> points = new List<Point>();
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private int strokeId = -1;
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private Vector3 virtualKeyPosition = Vector2.zero;
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private Rect drawArea;
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private RuntimePlatform platform;
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private int vertexCount = 0;
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private List<LineRenderer> gestureLinesRenderer = new List<LineRenderer>();
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private LineRenderer currentGestureLineRenderer;
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//GUI
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private string message;
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private bool recognized;
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// Use this for initialization
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void Start () {
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platform = Application.platform;
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drawArea = new Rect(0, 0, Screen.width - Screen.width / 3, Screen.height);
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TextAsset[] gesturesXml = Resources.LoadAll<TextAsset>("GestureSet/10-stylus-MEDIUM/");
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foreach (TextAsset gestureXml in gesturesXml)
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trainingSet.Add(GestureIO.ReadGesture(gestureXml.text));
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}
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// Update is called once per frame
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void Update () {
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if (platform == RuntimePlatform.Android || platform == RuntimePlatform.IPhonePlayer) {
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}
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}
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if (Input.GetMouseButtonDown(0)) {
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points.Clear();
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++strokeId;
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}
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if (Input.GetMouseButton(0)) {
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points.Add(new Point(virtualKeyPosition.x, -virtualKeyPosition.y, strokeId));
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gestureOnScreen.position = WorldCoordinateForGesturePoint(virtualKeyPosition);
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if (drawArea.Contains(virtualKeyPosition)) {
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if (Input.GetMouseButtonDown(0)) {
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if (recognized) {
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recognized = false;
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points.Clear();
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foreach (LineRenderer lineRenderer in gestureLinesRenderer) {
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lineRenderer.SetVertexCount(0);
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Destroy(lineRenderer);
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}
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gestureLinesRenderer.Clear();
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}
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++strokeId;
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Transform tmpGesture = Instantiate(gestureOnScreenPrefab, transform.position, transform.rotation) as Transform;
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currentGestureLineRenderer = tmpGesture.GetComponent<LineRenderer>();
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gestureLinesRenderer.Add(currentGestureLineRenderer);
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vertexCount = 0;
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}
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if (Input.GetMouseButton(0)) {
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points.Add(new Point(virtualKeyPosition.x, -virtualKeyPosition.y, strokeId));
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currentGestureLineRenderer.SetVertexCount(++vertexCount);
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currentGestureLineRenderer.SetPosition(vertexCount - 1, WorldCoordinateForGesturePoint(virtualKeyPosition));
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}
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}
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if (Input.GetMouseButtonUp(0)) {
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}
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void OnGUI() {
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GUI.Box(drawArea, "Draw Area");
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GUI.Label(new Rect(10, Screen.height - 40, 500, 50), message);
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if (GUI.Button(new Rect(Screen.width - 100, 10, 100, 30), "Recognize")) {
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recognized = true;
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Gesture candidate = new Gesture(points.ToArray());
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Result gestureResult = PointCloudRecognizer.Classify(candidate, trainingSet.ToArray());
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Debug.Log(gestureResult.GestureClass);
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Debug.Log(gestureResult.Score);
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message = gestureResult.GestureClass + " " + gestureResult.Score;
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strokeId = -1;
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}
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}

‎README.md‎

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=========================
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[Web demo](http://depts.washington.edu/aimgroup/proj/dollar/pdollar.html).
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In the demo, only one point-cloud template is loaded for each of the 16 gesture types. You can add additional templates as you wish, and even define your own custom gesture templates.
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![](http://aymericlamboley.fr/blog/wp-content/uploads/2014/07/multistrokes.gif)
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About
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-----
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The [$P](http://depts.washington.edu/aimgroup/proj/dollar/pdollar.html) Point-Cloud Recognizer is a 2-D gesture recognizer designed for rapid prototyping of gesture-based user interfaces. In machine learning terms, $P is an instance-based nearest-neighbor classifier with a Euclidean scoring function, i.e., a geometric template matcher. $P is the latest in the dollar family of recognizers that includes [$1](http://depts.washington.edu/aimgroup/proj/dollar/index.html) for unistrokes and [$N](http://depts.washington.edu/aimgroup/proj/dollar/ndollar.html) for multistrokes. Although about half of $P's code is from $1, unlike both $1 and $N, $P does not represent gestures as ordered series of points (i.e., strokes), but as unordered point-clouds. By representing gestures as point-clouds, $P can handle both unistrokes and multistrokes equivalently and without the combinatoric overhead of $N. When comparing two point-clouds, $P solves the classic [assignment problem](http://en.wikipedia.org/wiki/Assignment_problem) between two bipartite graphs using an approximation of the [Hungarian algorithm](http://en.wikipedia.org/wiki/Hungarian_algorithm). The $P recognizer is distributed under the [New BSD License](http://en.wikipedia.org/wiki/BSD_licenses#3-clause_license_.28.22Revised_BSD_License.22.2C_.22New_BSD_License.22.2C_or_.22Modified_BSD_License.22.29) agreement.

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