3D Reconstruction of a Human Head

Stefania Cristina, Kenneth P. Camilleri

The problem of reconstructing the surface of an object in 3-dimensional space has been studied extensively over the years, with applications ranging from industrial product inspection, to robot guidance and 3-dimensional object modelling. The key factor in the acquisition of such 3-dimensional information is the principle of range measurement, or in simpler terms, the measurement of depth of an object’s surface relative to the position of a known point or plane in space.

Stereo vision is a well-known technique to extract the 3-dimensional information from pairs of images by relating the image coordinates of corresponding points that belong to the same object feature in 3-dimensional space. This is similar to the human binocular vision, where the brain receives two horizontally shifted images of a scene as captured by the eyes and merges them into a 3-dimensional monocular view by matching the similarities in the separate views. While the brain performs this fusion of images efficiently, stereo vision methods face several challenges in identifying similar features due to occluded parts and repetitively textured or untextured surface patches.

This research work concerns the development and implementation of a low-cost multiple-stereo 3-dimensional acquisition system, for the specific purpose of modelling a person’s head. Our work focuses on the investigation of data fusion algorithms that could exploit the data redundancy from multiple cameras to reduce occlusions and improve depth accuracy. Passive and active lighting techniques are combined together in order to address issues related to the reconstruction of repetitively textured patches on the face. Furthermore, techniques which permit an improvement in reconstruction resolution are also studied in order to obtain a reliable high-resolution 3-dimensional reconstruction of the person’s head.

This research work has been carried out during 3D-Head, a project funded by the Malta Council for Science and Technology through the National RTDI Programme (2005), in collaboration with Megabyte Ltd.

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