Being able to find the silhouette of an object is a very important front-end processing step for many high-level computervision techniques, such as Shape-from-Silhouette 3D reconstruction methods;object shape trackin...
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ISBN:
(纸本)9783642041457
Being able to find the silhouette of an object is a very important front-end processing step for many high-level computervision techniques, such as Shape-from-Silhouette 3D reconstruction methods;object shape tracking;and pose estimation. Graph cuts have been proposed as a method for finding very accurate silhouettes which can he used as input to such high level techniques, hut graph cuts are notoriously computation intensive and slow. Leading CPU implementations can extract a silhouette from a single QVGA image in PM milliseconds, with performance dramatically decreasing with increased resolution. Recent implementations have been able to achieve performance of milliseconds per image by exploiting the intrinsic properties of the lattice graphs and the hardware model of the CPU. However, these methods are restricted to a subclass of lattice graphs and are not generally applicable. We propose a novel method for graph cuts on the CPU which places no limits on graph configuration and which is able to achieve comparable real-time performance in online video processing scenarios.
this book constitutes the refereed proceedings of the International Workshop on Mesh processing in Medical image Analysis, MeshMed 2012, held in Nice, France, in October 2012 in conjunction with MICCAI 2012, the 15th ...
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ISBN:
(数字)9783642334634
ISBN:
(纸本)9783642334627
this book constitutes the refereed proceedings of the International Workshop on Mesh processing in Medical image Analysis, MeshMed 2012, held in Nice, France, in October 2012 in conjunction with MICCAI 2012, the 15th International conference on Medical image Computing and computer Assisted Intervention.
the book includes 16 submissions, 8 were selected for presentation along withthe 3 plenary talks representative of the meshing, and 8 were selected for poster presentations. the papers cover a broad range of topics, including statistical shape analysis and atlas construction, novel meshing approaches, soft tissue simulation, quad dominant meshing and mesh based shape descriptors. the described techniques were applied to a variety of medical data including cortical bones, ear canals, cerebral aneurysms and vascular structures.
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 two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International conference on computervision and imageprocessing. held in Jaipur, India, in September 2019...
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ISBN:
(数字)9789811540158
ISBN:
(纸本)9789811540141
this two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International conference on computervision and imageprocessing. held in Jaipur, India, in September 2019.;the 73 full papers and 10 short papers were carefully reviewed and selected from 202 submissions. the papers are organized according to the following topics:;Part I: Biometrics; computer Forensic; computervision; Dimension Reduction; Healthcare Information Systems; imageprocessing; image segmentation; Information Retrieval; Instance based learning; Machine Learning.;Part II: Neural Network; Object Detection; Object Recognition; Online Handwriting Recognition; Optical Character Recognition; Security and Privacy; Unsupervised Clustering.
the sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European conference on computervision, ECCV 2018, held in Munich, Germany, in September 2018.;the 776 re...
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ISBN:
(数字)9783030012496
ISBN:
(纸本)9783030012489
the sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European conference on computervision, ECCV 2018, held in Munich, Germany, in September 2018.;the 776 revised papers presented were carefully reviewed and selected from 2439 submissions. the papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.
Robustness is a key attribute of spread spectrum (SS) watermarking scheme. It is significantly deteriorated if one tries to achieve high embedding rate keeping other parameters unaltered. In literatures, typically var...
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Robustness is a key attribute of spread spectrum (SS) watermarking scheme. It is significantly deteriorated if one tries to achieve high embedding rate keeping other parameters unaltered. In literatures, typically various transformations like DFT, DCT, Fourier-Mellin and wavelet are used for SS multimedia watermarking but little studies have been attempted so far to see what are the possible factors which can improve robustness. the current paper has critically analyzed few such factors namely design of code pattern, proper signal decomposition suitable for data embedding, direction of decomposition, selection of regions for data embedding, signaling scheme, choice of modulation functions and embedding strength. Based on the observation, wavelet based SS watermarking scheme is proposed and improvement in robustness performance is verified through experimental results as well by mathematical analysis. (c) 2006 Elsevier B.V. All rights reserved.
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.
Studies of object detection and localization, particularly pedestrian detection have received considerable attention in recent times due to its several prospective applications such as surveillance, driving assistance...
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ISBN:
(纸本)9781450366151
Studies of object detection and localization, particularly pedestrian detection have received considerable attention in recent times due to its several prospective applications such as surveillance, driving assistance, autonomous cars, etc. Also, a significant trend of latest research studies in related problem areas is the use of sophisticated Deep Learning based approaches to improve the benchmark performance on various standard datasets. A trade-off between the speed (number of video frames processed per second) and detection accuracy has often been reported in the existing literature. In this article, we present a new but simple deep learning based strategy for pedestrian detection that improves this trade-off. Since training of similar models using publicly available sample datasets failed to improve the detection performance to some significant extent, particularly for the instances of pedestrians of smaller sizes, we have developed a new sample dataset consisting of more than 80K annotated pedestrian figures in videos recorded under varying traffic conditions. Performance of the proposed model on the test samples of the new dataset and two other existing datasets, namely Caltech Pedestrian Dataset (CPD) and CityPerson Dataset (CD) have been obtained. Our proposed system shows nearly 16% improvement over the existing state-of-the-art result.
the sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European conference on computervision, ECCV 2018, held in Munich, Germany, in September 2018.;the 776 re...
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ISBN:
(数字)9783030012281
ISBN:
(纸本)9783030012274
the sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European conference on computervision, ECCV 2018, held in Munich, Germany, in September 2018.;the 776 revised papers presented were carefully reviewed and selected from 2439 submissions. the papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.
the sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European conference on computervision, ECCV 2018, held in Munich, Germany, in September 2018.;the 776 re...
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ISBN:
(数字)9783030012199
ISBN:
(纸本)9783030012182
the sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European conference on computervision, ECCV 2018, held in Munich, Germany, in September 2018.;the 776 revised papers presented were carefully reviewed and selected from 2439 submissions. the papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.
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