In Mixed Reality scenarios, background replacement is a common way to immerse a user in a synthetic environment. Properly identifying the background pixels in an image or video is a difficult problem known as matting. Proper alpha mattes usually come from human guidance, special hardware setups, or color dependent algorithms. This is a consequence of the under-constrained nature of the per pixel alpha blending equation. While the field of natural image matting has made progress finding a least squares solution for an alpha matte, the generation of trimaps, indicating regions of known foreground and background pixels, normally requires human interaction or offline computation. We overcome these limitations by combining a low fidelity depth i...