Breast cancer is one of the most prevalent forms of cancer in the world today. The search for effective treatment and screening methods is a highly active area of research. The Digital Image-based Elasto-Tomography (DIET) project is a new breast cancer screening system under development, where surface motion from the mechanically actuated breast is measured in 3D, and used as input to an inverse problem solving for breast elasticity. Cancerous lesions appear as high contrast features, being an order of magnitude stiffer than healthy tissue. The 3D motion capture is measured by an array of digital cameras using computer vision techniques. This paper presents a computer vision imaging system for the capture of 3D breast surface motion for the DIET system, including the image acquisition system, camera calibration, and 3D surface and motion reconstruction. Results are presented for experiments performed with silicone gel phantoms, with conditions designed to replicate the clinical procedure. Full 3D surface motion is successfully captured using an array of five cameras. Some successful results from the DIET inverse problem are also presented to demonstrate the viability of the system in practice.