In this work, we implement a real-time visual tracker that targets the position and 3D pose of objects in video sequences, specifically faces. Using Stream Processors for performing the computations as well as efficient Sparse-Template-based particle filtering allows us to achieve real-time processing even when tracking multiple objects simultaneously in highresolution video frames. Stream processing is a relatively new computing paradigm that permits the expression and execution of data-parallel algorithms with great efficiency and minimum effort. Using a GPU (Graphics Processing Unit, a consumer-grade Stream Processor) and the NVIDIA CUDATM technology, we can achieve real-time performance even when tracking multiple objects in high-quality videos.