ARKit 3的身体追踪算法可以通过以下步骤解决:
import ARKit
import Vision
let session = ARSession()
let configuration = ARWorldTrackingConfiguration()
configuration.frameSemantics.insert(.personSegmentationWithDepth)
session.run(configuration)
extension ViewController: ARSessionDelegate {
func session(_ session: ARSession, didUpdate frame: ARFrame) {
guard let personSegmentationBuffer = frame.segmentationBuffer,
let personSegmentationMask = try? personSegmentationBuffer.createMask(colorScheme: .gray),
let depthMap = frame.sceneDepth?.depthMap
else {
return
}
let bodyTrackingRequest = VNDetectHumanBodyPoseRequest(completionHandler: handleBodyTracking)
let bodyTrackingHandler = VNImageRequestHandler(cvPixelBuffer: depthMap, orientation: .right, options: [:])
do {
try bodyTrackingHandler.perform([bodyTrackingRequest])
} catch {
print("Error performing body tracking request: \(error)")
}
}
func handleBodyTracking(request: VNRequest, error: Error?) {
guard let observations = request.results as? [VNHumanBodyPoseObservation] else {
return
}
// 处理每个人体姿势的结果
for observation in observations {
// 提取关键点
guard let recognizedPoints = try? observation.recognizedPoints(.all) else {
continue
}
// 处理关键点数据
for (_, point) in recognizedPoints where point.confidence > 0.3 {
let normalizedPoint = CGPoint(x: CGFloat(point.location.x), y: CGFloat(point.location.y))
let unprojectedPoint = self.unprojectPoint(normalizedPoint)
// 在AR场景中使用unprojectedPoint进行相应的操作
// ...
}
}
}
}
func unprojectPoint(_ point: CGPoint) -> SCNVector3 {
let hitTestResults = sceneView.hitTest(point, types: .featurePoint)
guard let result = hitTestResults.first else {
return SCNVector3Zero
}
return SCNVector3(result.worldTransform.columns.3.x, result.worldTransform.columns.3.y, result.worldTransform.columns.3.z)
}
这样,你就可以在ARKit 3中使用身体追踪算法,提取人体关键点的位置信息,并在AR场景中进行相应的操作。