Title :
A shape-from-shading method of polyhedral objects using prior information
Author :
Shimodaira, Hisashi
Author_Institution :
Dept. of Inf. & Commun., Bunkyo Univ., Chigasaki, Japan
fDate :
4/1/2006 12:00:00 AM
Abstract :
We propose a new method for recovering the 3D shape of a polyhedral object from its single 2D image using the shading information contained in the image and the prior information on the object. In a strict sense, we cannot recover the shape of a polyhedron from an incorrect line drawing, even if it is practically almost correct. In order to overcome this problem, we propose a flexible face positioning method that can permit inconsistencies in the recovered shape that arise from vertex-position errors contained in incorrect line drawings. Also, we propose to use prior information about the horizontality and verticality of special faces and the convex and concave properties of the edges in order to attain good solutions and present a method of formulating such prior information as physical constraints. The shape-from-shading method is formulated as a minimization problem of a nonlinear cost function with the nonlinear constraints and its solution is searched by a global optimization algorithm. In the experiments with a synthetic image and three kinds of real images, shapes that are similar to those of the actual objects were recovered in all cases. As a result, the proposed method has proven to be effective in the shape recovery of simple-shape polyhedral objects.
Keywords :
image processing; minimisation; nonlinear functions; 3D shape recovery; flexible face positioning method; global optimization algorithm; incorrect line drawings; minimization problem; nonlinear constraints; nonlinear cost function; physical constraints; prior information; shading information; shape-from-shading method; simple-shape polyhedral objects; single 2D image; synthetic image; vertex-position errors; Computer Society; Computer vision; Constraint optimization; Cost function; Image analysis; Image recognition; Layout; Minimization methods; Shape; Stereo vision; 3D/stereo scene analysis; Vision and scene understanding; modeling and recovery of physical attributes; scene analysis; shading.; shape; Algorithms; Artificial Intelligence; Cluster Analysis; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2006.67