Synthetic hand pose data has been frequently used in vision based hand gesture recognition. However existing synthetic hand pose generators are not able to detect intersection between various hand parts and can synthe...
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ISBN:
(纸本)9784901122160
Synthetic hand pose data has been frequently used in vision based hand gesture recognition. However existing synthetic hand pose generators are not able to detect intersection between various hand parts and can synthesize self intersecting poses. Using such data may lead to learning wrong models. We propose a method to eliminate self intersecting synthetic hand poses by accurately detecting intersections between various hand parts. We model each hand part as a convex hull and calculate pairwise distance between the parts, labeling any pair with a negative distance as intersecting. A hand pose with at least one pair of intersecting parts is labeled as self intersecting. We show experimentally that our method is very accurate and performs better than existing techniques. We also show that it is fast enough for offline data generation.
this paper presents an extended method of guided image filtering (GF) for high-dimensional signals and proposes various applications for it. the important properties of GF include edge-preserving filtering, local line...
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ISBN:
(纸本)9783319648705;9783319648699
this paper presents an extended method of guided image filtering (GF) for high-dimensional signals and proposes various applications for it. the important properties of GF include edge-preserving filtering, local linearity in a filtering kernel region, and the ability of constant time filtering in any kernel radius. GF can suffer from noise caused by violations of the local linearity when the kernel radius is large. Moreover, unexpected noise and complex textures can further degrade the local linearity. We propose high-dimensional guided image filtering (HGF) and a novel framework named combining guidance filtering (CGF). Experimental results show that HGF and CGF can work robustly and efficiently for various applications in imageprocessing.
Texture synthesis is the hot research topic in the field of computervision, computergraphics and imageprocessing. Sample-based texture synthesis method has been proposed and becomes a new texture tiling technique w...
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ISBN:
(纸本)9781538632215
Texture synthesis is the hot research topic in the field of computervision, computergraphics and imageprocessing. Sample-based texture synthesis method has been proposed and becomes a new texture tiling technique withthe development of the texture mapping and procedural texture synthesis. image Quilting stitching algorithm is an ideal algorithm for the texture stitching. In this article, by using the image Quilting algorithm to finish the texture transfer and stitch the objective texture image, whose texture style does not exist in the initial image. In experiments, by transferring the style of the human face image and character image respectively, verified the effectiveness of this proposed algorithm.
Computed Tomography (CT) is one of the significant research areas in medical image analysis. One of the main aspects of CT that researchers remain focused, is on reducing the dosage as Xrays are generally harmful to h...
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ISBN:
(纸本)9783319681245;9783319681238
Computed Tomography (CT) is one of the significant research areas in medical image analysis. One of the main aspects of CT that researchers remain focused, is on reducing the dosage as Xrays are generally harmful to human bodies. In order to reduce radiation dosage, compressed sensing (CS) based methodologies appear to be promising. the basic premise is that medical images have inherent sparsity in some transformation domain. As a result, CS provides the possibility of recovering a high quality image from fewer projection data. In general, the sensing matrix in CT is generated from Radon projections by appropriately sampling the radial and angular parameters. In our work, by restricting the number of such parameters, we generate an under-determined linear system involving projection (Radon) data and a sparse sensing matrix, bringing thereby the problem into CS framework. Among various recent solvers, the Split-Bregman iterative scheme has of late become popular due to its suitability for solving a wide variety of optimization problems. Intending to exploit the underlying structure of sensing matrix, the present work analyzes its properties and finds a banded structure for an associated intermediate matrix. Using this observation, we simplify the Split-Bregman solver, proposing thereby a CT-specific solver of low complexity. We also provide the efficacy of proposed method empirically.
Interactive image segmentation is a fundamental task in many applications in graphics, imageprocessing, and computational photography. Many leading methods formulate elaborated energy functionals, achieving high perf...
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ISBN:
(纸本)9783319541815;9783319541808
Interactive image segmentation is a fundamental task in many applications in graphics, imageprocessing, and computational photography. Many leading methods formulate elaborated energy functionals, achieving high performance with reflecting human's intention. However, they show limitations in practical usage since user interaction is labor intensive to obtain segments efficiently. We present an interactive segmentation method to handle this problem. Our approach, called point cut, requires minimal point supervision only. To this end, we use off-the-shelf object proposal methods that generate object candidates with high recall. Withthe single point supervision, foreground appearance can be estimated with high accuracy, and then integrated into a graph cut optimization to generate binary segments. Intensive experiments show that our approach outperforms existing methods for interactive object segmentation both qualitatively and quantitatively.
Alignment of 3D human body scans is a challenging problem in computervision with various applications. While being extensively studied for the mesh based case, it is still involved if scans lack topology. In this pap...
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ISBN:
(纸本)9784901122160
Alignment of 3D human body scans is a challenging problem in computervision with various applications. While being extensively studied for the mesh based case, it is still involved if scans lack topology. In this paper, we propose a practical solution to the point cloud based registration of 3D human scans and a 3D human template. We adopt recent advances in point set registration with prior matches and design a fully automated registration framework. Our framework consists of several steps including establishment of prior matches, alignment of point clouds into a common reference frame, global non-rigid registration, partial non-rigid registration, and a post-processing step. We can handle large point clouds with significant variations in appearance automatically and achieve high registration accuracy which is shown experimentally. Finally, we demonstrate a pipeline for treatment of social pathologies with animatable virtual avatars as an exemplary real-world application of the new framework. [graphics] .
Convolutional Neural Network(CNN) based semantic segmentation require extensive pixel level manual annotation which is daunting for large microscopic images. the paper is aimed towards mitigating this labeling effort ...
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ISBN:
(纸本)9781538607336
Convolutional Neural Network(CNN) based semantic segmentation require extensive pixel level manual annotation which is daunting for large microscopic images. the paper is aimed towards mitigating this labeling effort by leveraging the recent concept of generative adversarial network(GAN) wherein a generator maps latent noise space to realistic images while a discriminator differentiates between samples drawn from database and generator. We extend this concept to a multi task learning wherein a discriminator-classifier network differentiates between fake/real examples and also assigns correct class labels. though our concept is generic, we applied it for the challenging task of vessel segmentation in fundus images. We show that proposed method is more data efficient than a CNN. Specifically, with150K, 30K and 15K training examples, proposed method achieves mean AUC of 0.962, 0.945 and 0.931 respectively, whereas the simple CNN achieves AUC of 0.960, 0.921 and 0.916 respectively.
Music transcription refers to the process of analyzing a piece of music to generate a sequence of constituent notes and their duration. Transcription of music from audio signals is fraught with problems due to auditor...
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ISBN:
(纸本)9781450347532
Music transcription refers to the process of analyzing a piece of music to generate a sequence of constituent notes and their duration. Transcription of music from audio signals is fraught with problems due to auditory interference such as ambient noise, multiple instruments playing simultaneously, accompanying vocals or polyphonic sounds. For several instruments, there exists added information for music transcription which can be derived from a video sequence of the instrument as it is being played. this paper proposes a method to utilize this visual information for the case of keyboard-like instruments to generate a transcript automatically, by analyzing the video frames. We present encouraging results under varying lighting conditions on different song sequences played out on a keyboard.
We present a novel algorithm to remove near regular, fence or wire like foreground patterns from an image. the fence detection or fence removal algorithms, developed so far, have poor performance in detecting the fenc...
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ISBN:
(纸本)9781450347532
We present a novel algorithm to remove near regular, fence or wire like foreground patterns from an image. the fence detection or fence removal algorithms, developed so far, have poor performance in detecting the fence. We use signal demixing to utilize the sparsity and regularity property of fences to detect them. Results demonstrate the effectiveness of our technique as compared to other state of the art techniques.
image Hallucination has many applications in areas such as imageprocessing, computational photography and image fusion. In this paper, we present an image Hallucination technique based on the template (patch) matchin...
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ISBN:
(纸本)9781450347532
image Hallucination has many applications in areas such as imageprocessing, computational photography and image fusion. In this paper, we present an image Hallucination technique based on the template (patch) matching from the database of time lapse images and learned locally affine model. Template based techniques suffer from blocky artifacts. So, we propose two approaches for imposing consistency criteria across neighbouring patches in the form of regularization. We validate our Color transfer technique by hallucinating a variety of natural images at different times the day. We compare the proposed approach with other state of the art techniques of example image based color transfer and show that the images obtained using our approach look more plausible and natural.
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