要實現手勢識別，可以使用MediaPipe庫中的Hand Tracking和Hand Landmark模塊。以下是一個簡單的示例代碼，演示如何使用MediaPipe實現手勢識別：

import android.os.Bundle;
import androidx.annotation.NonNull;
import androidx.appcompat.app.AppCompatActivity;
import com.google.mediapipe.components.CameraHelper;
import com.google.mediapipe.components.PermissionHelper;
import com.google.mediapipe.formats.proto.LandmarkProto.NormalizedLandmarkList;
import com.google.mediapipe.formats.proto.LandmarkProto.NormalizedLandmark;
import com.google.mediapipe.solutions.hands.HandLandmark;
import com.google.mediapipe.solutions.hands.Hands;
import com.google.mediapipe.solutions.hands.HandsResult;
import com.google.mediapipe.solutions.hands.HandsOptions;
import com.google.mediapipe.framework.AndroidAssetUtil;
import com.google.mediapipe.framework.Packet;
import com.google.mediapipe.framework.PacketGetter;
import com.google.mediapipe.framework.TextureFrame;
import com.google.mediapipe.glutil.EglManager;
import com.google.mediapipe.glutil.GlTextureFrame;
import com.google.mediapipe.components.TextureFrameConsumer;

public class MainActivity extends AppCompatActivity {
    private static final String TAG = "MainActivity";
    private static final String BINARY_GRAPH_NAME = "hand_tracking_mobile.pb";
    private static final String INPUT_VIDEO_STREAM_NAME = "input_video";
    private static final String OUTPUT_VIDEO_STREAM_NAME = "output_video";
    private static final String LANDMARKS_STREAM_NAME = "hand_landmarks";
    private static final CameraHelper.CameraFacing CAMERA_FACING = CameraHelper.CameraFacing.FRONT;
    private Hands hands;
    private CameraHelper cameraHelper;
    private TextureFrameConsumer videoConsumer;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);

        EglManager eglManager = new EglManager(null);
        hands = new Hands(this, HandsOptions.builder().build());
        hands.setInputSidePackets(new Packet[] {});

        cameraHelper = new CameraHelper(this, CAMERA_FACING,  /*surfaceTexture=*/ null,  /*previewDisplayView=*/ null);
        cameraHelper.setOnCameraStartedListener(surfaceTexture -> {
            videoConsumer = new TextureFrameConsumer() {
                @Override
                public void onNewFrame(TextureFrame textureFrame) {
                    processFrame(textureFrame);
                }
            };
            cameraHelper.setFrameProcessor(videoConsumer, eglManager);
        });

        cameraHelper.startCamera();
    }

    private void processFrame(TextureFrame textureFrame) {
        HandsResult handsResult = hands.process(textureFrame);
        if (handsResult.hasHandLandmarks()) {
            NormalizedLandmarkList landmarks = handsResult.getHandLandmarks();
            processHandLandmarks(landmarks);
        }
    }

    private void processHandLandmarks(NormalizedLandmarkList landmarks) {
        for (NormalizedLandmark landmark : landmarks.getLandmarkList()) {
            float x = landmark.getX();
            float y = landmark.getY();
            float z = landmark.getZ();
            // Do something with the landmark coordinates
        }
    }

    @Override
    protected void onResume() {
        super.onResume();
        cameraHelper.startCamera();
    }

    @Override
    protected void onPause() {
        super.onPause();
        cameraHelper.stopCamera();
    }

    @Override
    protected void onDestroy() {
        super.onDestroy();
        hands.close();
    }
}

在這個示例代碼中，我們首先創建了一個Hands實例，并設置了HandTracking的參數。然后通過CameraHelper來獲取攝像頭的幀，將每一幀傳遞給Hands實例的process方法進行手勢識別。最后，我們可以從HandsResult中獲取手部的關鍵點坐標，并進行進一步的處理。

請注意，此示例只是一個簡單的演示，實際項目中可能需要根據具體的需求進行調整和優化。您可以查閱MediaPipe的官方文檔以獲取更多詳細信息和示例代碼。