In real-world applications, factors such as illumination variation, occlusion, and poor image quality, etc. make head detection and pose estimation much more challenging. In this paper, we propose a multi-level structured hybrid forest (MSHF) for joint head detection and pose estimation. Our method extends the hybrid framework of classification and regression forests by introducing multi-level splitting functions and multi-structural features. Multi-level splitting functions are used to construct trees in different layers of MSHF. Multi-structured features are.extracted from randomly selected ...
