Biological Cybernetics
Shape from texture: general principle
Artificial Intelligence
Shape From Texture: Integrating Texture-Element Extraction and Surface Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from texture using the Wigner distribution
Computer Vision, Graphics, and Image Processing
Shape from shading with a generalized reflectance map model
Computer Vision and Image Understanding
Shape from Shading with a Linear Triangular Element Surface Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Scale Filtering: A General Method for Obtaining Shape From Texture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Obtaining surface orientation from texels under perspective projection
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Shape from Texture without Boundaries
International Journal of Computer Vision
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In this research, we propose a new iterative shape from texture (SFT) algorithm which extracts accurate surface depth information of a curved object covered with fairly homogeneous texture directly. The shape information can be inferred from the rate of texture distortion depicted in an image, and therefore the modeling of the projection and surface geometry as well as the estimation of local texture variation are crucial in obtaining accurate surface shape of an object. By introducing semi-perspective projection camera model and a parametric surface model, we establish a new SFT problem formulation called the textural irradiance equation which relates the local texture density called textural intensity to finite surface parameters. Moreover, by adopting an adaptive multiscale filtering scheme for local texture density estimation, in which the scale or frequency band of a local edge filter is chosen adaptively according to the local shape information, we greatly enhance the accuracy of the estimation of the projected local texture densities, and the final reconstructed shape. We demonstrate the performance of the proposed algorithm by the test with several synthetic and real texture images.