Perceiving 3D structure in natural images is an immense computational challenge for the visual system. While many previous studies focused on perception of rigid objects, we applied a novel method common set non-rigid objects—static human body world. Perception particularly challenging due to various joint articulations with different frequency occurrence, and appearance variations from changes...

Three-Dimensional Reconstruction of Fire from Images Samuel William Hasinoff Master of Science Graduate Department of Computer Science University of Toronto 2002 Interesting visual simulations have been proposed for physical phenomena such as fire and smoke, but scant attention has been paid to reconstructing models of these phenomena from multiple images of real scenes. Here we study the probl...

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the threedimensional (3D) conformation of a protein, yet it remains labor intensive and relies on an expert's ability to derive and evaluate a protein scene model. In this paper, the problem of protein structure determination is ...

Modeling of three-dimensional (3D) objects from image sequences is a challenging problem and has been a research topic for many years. Important theoretical and algorithmic results were achieved that allow to extract even complex 3D models of scenes from sequences of images. One recent effort has been to reduce the amount of calibration and to avoid restrictions on the camera motion. In this co...