We present a method for transferring the identity of a given subject to a target image for try-on experience of clothes. Instead of fitting the garment to the user's model, we clone the user's identity into a catalogue of model images wearing the desired garments. This process involves replacing the head and hair style, relighting and adjusting the skin color, and modifying the body dimensions. We present an accurate segmentation procedure for human heads that separates three semantic parts: face, hair, and background. We use a tri-kernel statistical model based on textons and segment using graph cut. Using an offline simple training phase the extracted head can be cloned automatically into photos of catalogue models. The skin color is adjusted according to a color statistical model based on a Gaussian mixture model, and the head is relighted using a Spherical Harmonics model. Lastly, the body dimensions are warped to fit the user's dimensions using a parametric 3D human model. This creates high quality composite images imitating the identity of the user in the desired garment. We demonstrate a number of examples of such realistic results, and present a study that supports the quality of our results.