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Reconstruction of a three-dimensional scene using images taken from two views is possible if the relative pose of the cameras is known. A traditional approach to estimating the pose of the cameras uses eight pairs of corresponding points and involves the solution of a set of homogeneous equations. We propose a multi-layered feedforward network solution. Empirical results demonstrate the feasibility...
The adaptive disparity filter is refined, along with the monocular feature filter designed based on neuron dynamics, and a new stereopsis model is set up in this study. The disparities of the matched binocular features in stereo image pair are detected by the adaptive disparity filter, and removed by the monocular feature filter, only leaving those unmatched monocular features to be added to all depth...
The camera model could be approximated by a set of linear models defined on a set of local receptive fields regions. Camera calibration could then be a learning procedure to evolve the size and shape of every receptive field as well as parameters of the associated linear model. For a multi-camera system, its unified model is obtained from a fusion procedure integrated with all linear models weighted...
The accuracy of 3D measurements of objects is highly affected by the errors originated from camera calibration. Therefore, camera calibration has been one of the most challenging research fields in the computer vision and photogrammetry recently. In this paper, an Artificial Neural Network Based Camera Calibration Method, NBM, is proposed. The NBM is especially useful for back-projection in the applications...
A camera calibration method based on a nonlinear modeling function of an artificial neural network (ANN) is proposed in this paper. With the application of the nonlinear mapping feature of an ANN, the proposed method successfully finds the relationship between image coordinates without explicitly calculating all the camera parameters, including position, orientation, focal length, and lens distortion...
A novel intelligent approach into 3D freeform surface reconstruction from planar sketches is proposed. A multilayer perceptron (MLP) neural network is employed to induce 3D freeform surfaces from planar freehand curves. Planar curves were used to represent the boundaries of a freeform surface patch. The curves were varied iteratively and sampled to produce training data to train and test the neural...
In volume data visualization, the classification is used to determine voxel visibility and is usually carried out by transfer functions that define a mapping between voxel value and color/opacity. The design of transfer functions is a key process in volume visualization applications. However, one transfer function that is suitable for a data set usually dose not suit others, so it is difficult and...
In this paper, we present a novel real-time approach to synthesizing 3D character animations of required style by adjusting a few parameters or scratching mouse cursor. Our approach regards learning captured 3D human motions as parametric Gaussians by the self-organizing mixture network (SOMN). The learned model describes motions under the control of a vector variable called the style variable, and...
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