Improving image resolution has broad applications and is an important research topic. Recently, a hybrid method Adaptive Sparse Domain Selection (ASDS) combining a reconstruction-basedmethod and an example-based meth...
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Improving image resolution has broad applications and is an important research topic. Recently, a hybrid method Adaptive Sparse Domain Selection (ASDS) combining a reconstruction-basedmethod and an example-based method has been proposed to take advantage of the two, but may not reconstruct sufficient details. In this study, the authors propose to improve ASDS: Zeyde's method is first used to obtain an intermediate image with high-frequency details, and then the obtained image is used to replace the autoregressive model of ASDS as the example-based term. In addition, the authors may split the input image into patches and use different parameter settings for the patches of different amount of details. Experimental results demonstrate the improved hybrid methods can produce high-quality images quantitatively and perceptually.
the example-based method for generating realistic, controllable human models was presented. Users are assisted in automatically generating modifying an example body data by controlling the parameters provided. The exa...
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Fabric or foam sheet moulding is an important manufacturing technique for the apparel industry, in particular for bra production. It is the most economical and convenient method to seamlessly form a garment part into ...
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Fabric or foam sheet moulding is an important manufacturing technique for the apparel industry, in particular for bra production. It is the most economical and convenient method to seamlessly form a garment part into a specified 3D shape. This paper proposes an example-based method for designing moulded bra cups. In this study, a total of 10 typical moulded bra cup specimens were scanned using the Steinbichler Comet white light scanner. Parameterization based remeshing and registration algorithm was used to characterize the 3D shapes of the convex surface of the scanned bra cups. Using an example-based method, virtual master moulds were constructed based on the 3D surfaces of the investigated bra cups after eliminating the style lines and size differences. Then a new bra cup design can be developed from the master mould, either by drawing the style lines in the virtual environment or using scissors to cut the moulded plastic shot along the desired style lines. Different sizes can also be made by grading the wire frame model in 3D manner. The present method will provide a scientific tool for the product development of new bra cups which was conventionally very time-consuming and ineffective.
In this paper, an improved example-driven symbol recognition algorithm is proposed for CAD engineering drawings. First, in order to represent the structure of symbols more clearly and simply, we involve the text entit...
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In this paper, an improved example-driven symbol recognition algorithm is proposed for CAD engineering drawings. First, in order to represent the structure of symbols more clearly and simply, we involve the text entity as one of the basic elements and redefine the relation representation mechanism, which is the foundation for the following algorithms. Then, the structure graph and a constrained tree can be established automatically for the target symbol, using the knowledge acquisition algorithm. In this process, the highest priority element is considered as the key feature, which will be regarded as the root node of the tree. The sequence of breadth first traveling will be recorded to be the recognition rule and saved in the symbol library. In the recognition process, the nodes with the same type as the key features can be located first in the drawing. Unnecessary matching calculations would be greatly reduced because of the accurate location. The other elements around. which satisfy the topology structure of the constrained tree, will be found next. The target symbol is recognized if all of the elements and constraints in the tree are found. Moreover, an extra preprocessing analysis approach is proposed to address repeat modes in a symbol. Thus, similar symbols can be recognized by one rule. We evaluate the proposed approach on the GREC databases and the real engineering drawings. The experimental results validate its effectiveness and efficiency. (C) 2012 Elsevier Ltd. All rights reserved.
Contrast enhancement is a very important problem in image processing. The key issue is how to assign correct enhancement levels for the local regions in an image, which makes previous methods incur much artifacts, e.g...
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Contrast enhancement is a very important problem in image processing. The key issue is how to assign correct enhancement levels for the local regions in an image, which makes previous methods incur much artifacts, e.g., over-enhancement, halo. In this paper, an example-based contrast enhancement algorithm is proposed, which works in the gradient domain. We utilize GMM model to describe the gradient distribution of an image. Then a GMM-based gradient mapping method is proposed to transfer the gradient of a reference image to the source image. The enhanced image is obtained by solving a Poisson equation defined by the altered gradient. Experimental results show the effectiveness and robustness of our method.
In this paper, we propose an efficient pose machine using Parameter-Sensitive Hashing(PSH) techniques. based on the original pose machine, which is a sequential prediction framework, we employ the Convolutional Neural...
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ISBN:
(纸本)9781538619797;9781538619780
In this paper, we propose an efficient pose machine using Parameter-Sensitive Hashing(PSH) techniques. based on the original pose machine, which is a sequential prediction framework, we employ the Convolutional Neural Network(CNN)to extract features. To handle the high dimensional feature vectors and conduct similarity search efficiently, we use the Parameter-Sensitive Hashing Function(PSHF) to map the feature vectors into binary values. The property of the PSHF ensures that the collisions happen when two vectors are near to each other and the search can be completed in a fractional power time. We apply our approach to the popular datasets including LSP and FLIC and make a comparison with previous methods based on a criterion of strict Percentage of Correct Parts(PCP).Experimental results reflect that our approach outperforms previous methods in accuracy.
In this paper, an approach to the introductory programming training and its core elements are presented. The main challenge was in suggesting the updates in the introductory training appropriate for students without p...
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In this paper, an approach to the introductory programming training and its core elements are presented. The main challenge was in suggesting the updates in the introductory training appropriate for students without previous knowledge or experience that will be valuable for their further professional growth. The core curriculum for students in computer science and IT are courses in programming languages and environments. The content, form and teaching method for them should correspond to the state of the art in computer science and industry, taking into account trends in programming languages, technologies, development methodologies. The paper provides a description of changes in content and method of teaching the course "Algorithmization and Programming of Solutions" offered to the first year students. (C) 2017 The Authors. Published by Elsevier B.V.
More image patches in a training set making it more time-consuming has become a holdback of the real-time application of example-based super-resolution. The paper proposes a method which clusters these training set to...
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ISBN:
(纸本)9780819483294
More image patches in a training set making it more time-consuming has become a holdback of the real-time application of example-based super-resolution. The paper proposes a method which clusters these training set to accelerate the procedure. Before the super-resolution, a clustering method is used to partition the middle-frequency components in the training set into some subsets. During super-resolution, the distances between each matching patch of low-resolution image and each subset of training set are computed. The subset with the minimum distance is selected to carry out farther matching. This procedure goes along until a most matching patch is found. The high-frequency patch within the training set relevant to the found matching patch is selected as the researching output, which is used for super-resolution of objective image. Two examples are use to illustrate the performance of the proposed algorithm, one using a factitious image obtained by blurring and down-sampling an original image, and another using directly a true image. The results show the proposed method can reduce effectively the computational complexity.
This paper proposes a framework that utilizes skinning decomposition to automatically generate facial rigging from 4D expressions. The framework inputs a predefined rigging template and an actor's 4D facial expres...
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ISBN:
(纸本)9798400701085
This paper proposes a framework that utilizes skinning decomposition to automatically generate facial rigging from 4D expressions. The framework inputs a predefined rigging template and an actor's 4D facial expressions, including a neutral expression, as well as a group of arbitrary expressions. The output includes not only the linear blend skinning weights and joint positions of the actor's head mesh but also other facial components such as teeth and eyes. Compared to traditional methods, this paper applies a soft constraint to optimize joint positions and imposes a fixed sparsity distribution constraint to improve weight distribution. To further enhance rigging efficiency, this paper leverages GPU expression-parallel and CPU vertex-parallel strategies for joint transformation and weight updates, respectively. The experiments show that the proposed method generates high-fidelity facial rigging that outperforms existing solutions in terms of computational speed, joint position correctness, weight distribution correctness, or computational cost.
In this paper, we propose an improved version of the neighbor embedding super-resolution (SR) algorithm proposed by Chang et al. [Super-resolution through neighbor embedding, in Proc. 2004 IEEE Computer Society Conf. ...
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In this paper, we propose an improved version of the neighbor embedding super-resolution (SR) algorithm proposed by Chang et al. [Super-resolution through neighbor embedding, in Proc. 2004 IEEE Computer Society Conf. Computer Vision and Pattern Recognition(CVPR), Vol. 1 (2004), pp. 275-282]. The neighbor embedding SR algorithm requires intensive computational time when finding the K nearest neighbors for the input patch in a huge set of training samples. We tackle this problem by clustering the training sample into a number of clusters, with which we first find for the input patch the nearest cluster center, and then find the K nearest neighbors in the corresponding cluster. In contrast to Chang's method, which uses Euclidean distance to find the K nearest neighbors of a low-resolution patch, we define a similarity function and use that to find the K most similar neighbors of a low-resolution patch. We then use local linear embedding (LLE) [S. T. Roweis and L. K. Saul, Nonlinear dimensionality reduction by locally linear embedding, Science 290(5500) (2000) 2323-2326] to find optimal coefficients, with which the linear combination of the K most similar neighbors best approaches the input patch. These coefficients are then used to form a linear combination of the K high-frequency patches corresponding to the K respective low-resolution patches (or the K most similar neighbors). The resulting high-frequency patch is then added to the enlarged (or up-sampled) version of the input patch. Experimental results show that the proposed clustering scheme efficiently reduces computational time without significantly affecting the performance.
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