I will build pose estimation sports analytics using ai computer vision

Understanding athlete movement is essential for elite performance. I specialize in pose estimation sports and sports performance analysis using AI sports analytics and sports computer vision.

Using Python computer vision, OpenCV sports analysis, and YOLO object detection, I build pipelines for player detection tracking combined with advanced pose estimation sports models. This enables deep sports data analysis for movement efficiency, injury prevention, and skill optimization.

My systems support football match analysis, basketball player tracking, and cricket analytics AI with precise joint tracking and motion analysis. With AI video processing and video analytics AI, raw footage becomes actionable biomechanics insight.

Advanced solutions integrate TensorFlow computer vision and PyTorch computer vision for deep learning computer vision, facial recognition AI, and optional athlete face recognition for personalized analytics. These systems scale to real-time object detection environments and research-grade datasets.

Ideal for coaches, sports scientists, startups, and rehabilitation platforms seeking intelligent sports AI solutions.