A Markerless Motion Measurement Method for Sport Climbing Using a Single RGB-D Camera and ICP-Based Model Fitting

Quantitative motion analysis is important for understanding the characteristics of climbing movement and for providing objective feedback in sport climbing. Although optical motion capture systems can measure three-dimensional body motion with high accuracy, their application to climbing is limited by the need for markers, multiple cameras, and a controlled measurement space, as well as by occlusion caused by the wall, holds, and body segments. A markerless measurement method using a compact sensor configuration would therefore be advantageous for analyzing climbing motion in more practical environments. This study presents a markerless three-dimensional motion measurement method for sport climbing using a single RGB-D camera and iterative closest point (ICP)-based body-part model fitting. The proposed method first separates the human region from the RGB image using image segmentation and then detects two-dimensional body keypoints using OpenPose. The detected keypoints are projected onto the depth image to reconstruct an initial three-dimensional posture. To refine the reconstructed posture, predefined body-part models are fitted to the segmented human point cloud using the ICP algorithm. The joint points included in the fitted body-part models are then used as the refined three-dimensional joint coordinates. Rather than relying solely on the accuracy of the image-based pose estimator, the proposed method introduces a model-based correction process that compensates for uncertainty in the initial keypoint-based reconstruction. This design aims to reduce the influence of background objects, unstable depth measurements, and incorrect or missing two-dimensional keypoints, which are common difficulties in climbing environments. The proposed method was quantitatively evaluated using five successfully completed trials from two participants under a low-occlusion condition and eight successfully completed trials from four participants under an occlusion-prone condition. The proposed method reduced the average three-dimensional RMSE across six representative body points relative to the initial RGB-D reconstruction under both conditions, with a more pronounced reduction under the occlusion-prone condition. The results indicate that ICP-based body-part model fitting is a useful correction step for single-camera RGB-D motion measurement in sport climbing.