⊲ Cannot Handle Multi-Modality

We describe a generative approach to recover 3D human pose from image silhouettes. Our method is based on learning a shared low dimensional latent representation capable of generating both human pose and image observations through the GP-LVM [Law05] We learn a dynamical model over the latent space which allows us to disambiguate between ambiguous silhouettes by temporal consistency. The model has only two free parameters and requires no manual initialization