Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646635
Zhipeng Li, S. Ravishankar, Y. Long, J. Fessler
Penalized weight-least squares (PWLS) with basis material priors is a promising way to achieve high quality material decompositions for Dual-energy CT (DECT). This paper proposes a new method dubbed DECT-MULTRA for image domain DECT material decomposition that combines conventional PWLS estimation with regular-ization based on a mixed union of learned transforms (MULTRA) model. Our approach pre-learns from training data a common union of unitary transforms for all the basis materials’ patches, as well as a cross-material union of unitary transforms that captures relationships between the different basis material images. The proposed DECT-MULTRA algorithm efficiently obtains material decompositions by alternating between updating the material images and performing clustering of patches in the MULTRA model. Both these steps of the alternating algorithm have closed-form updates. Numerical experiments with the XCAT phantom show that the proposed method significantly improves image quality compared to the recent DECT-ST method that learns different sparsifying transforms for different basis materials and the DECT-EP approach that uses a non-adaptive edge-preserving hyperbola regularizer.
{"title":"LEARNED MIXED MATERIAL MODELS FOR EFFICIENT CLUSTERING BASED DUAL-ENERGY CT IMAGE DECOMPOSITION","authors":"Zhipeng Li, S. Ravishankar, Y. Long, J. Fessler","doi":"10.1109/GlobalSIP.2018.8646635","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646635","url":null,"abstract":"Penalized weight-least squares (PWLS) with basis material priors is a promising way to achieve high quality material decompositions for Dual-energy CT (DECT). This paper proposes a new method dubbed DECT-MULTRA for image domain DECT material decomposition that combines conventional PWLS estimation with regular-ization based on a mixed union of learned transforms (MULTRA) model. Our approach pre-learns from training data a common union of unitary transforms for all the basis materials’ patches, as well as a cross-material union of unitary transforms that captures relationships between the different basis material images. The proposed DECT-MULTRA algorithm efficiently obtains material decompositions by alternating between updating the material images and performing clustering of patches in the MULTRA model. Both these steps of the alternating algorithm have closed-form updates. Numerical experiments with the XCAT phantom show that the proposed method significantly improves image quality compared to the recent DECT-ST method that learns different sparsifying transforms for different basis materials and the DECT-EP approach that uses a non-adaptive edge-preserving hyperbola regularizer.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134400714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646442
Gaoang Wang, Jenq-Neng Hwang, Yiling Xu, Farron Wallace, Craig S. Rose
Image processing and analysis techniques have drawn increasing attention since they enable a non-extractive and non-lethal approach to fisheries survey. To measure the fish size and length accurately, a reliable segmentation result is required. However, there are two major challenges about the segmentation. One is that images may be blurred due to the spray of water on the camera lens, and the other is that some part of the fish body is out of the camera view. In this paper, we present an innovative and effective contour-based segmentation refinement and missing shape recovery method from an arbitrary initial segmentation. The refinement is processed from coarse level to fine level. At the coarse level, a weighted affine transform is estimated to align the entire fish contour of the initial segmentation with trained representative contours. At the finer and finest levels, we iteratively refine the contour segments to represent the poorly segmented or shape missing image. The proposed method shows promising results on segmentation and length measurement for both water drop images and images with part of the fish out of the camera view.
{"title":"Coarse-To-Fine Segmentation Refinement and Missing Shape Recovery for Halibut Fish","authors":"Gaoang Wang, Jenq-Neng Hwang, Yiling Xu, Farron Wallace, Craig S. Rose","doi":"10.1109/GlobalSIP.2018.8646442","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646442","url":null,"abstract":"Image processing and analysis techniques have drawn increasing attention since they enable a non-extractive and non-lethal approach to fisheries survey. To measure the fish size and length accurately, a reliable segmentation result is required. However, there are two major challenges about the segmentation. One is that images may be blurred due to the spray of water on the camera lens, and the other is that some part of the fish body is out of the camera view. In this paper, we present an innovative and effective contour-based segmentation refinement and missing shape recovery method from an arbitrary initial segmentation. The refinement is processed from coarse level to fine level. At the coarse level, a weighted affine transform is estimated to align the entire fish contour of the initial segmentation with trained representative contours. At the finer and finest levels, we iteratively refine the contour segments to represent the poorly segmented or shape missing image. The proposed method shows promising results on segmentation and length measurement for both water drop images and images with part of the fish out of the camera view.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131562811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sparse-code multiple-access (SCMA) is an effective non-orthogonal multiple-access (NOMA) technique, which ranks one of the most promising candidates for future wireless, because of its outstanding performance. However, most of the existing work prefers low-connectivity SCMA systems, which actually cannot fulfill their priorities for massive connection. The difficulties in designing suitable factor graph matrix are responsible for this situation. In this paper, we propose a design manner of factor graph matrix to realize SCMA with large-scale customers. Quasi-cyclic property with shifting is introduced in SCMA factor graph matrix, based on the rules and restrictions of SCMA design including the column weight and the overloading factor. For numerical analysis, we introduce a performance function to show the effectiveness of our proposed SCMA system, and the results reveal that our work are better than conventional ones.
{"title":"A LARGE-SCALE EXTENSION OF SPARSE-CODE MULTIPLE-ACCESS SYSTEM","authors":"Chao Yang, Shusen Jing, X. Liang, Zaichen Zhang, X. You, Chuan Zhang","doi":"10.1109/GlobalSIP.2018.8646492","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646492","url":null,"abstract":"Sparse-code multiple-access (SCMA) is an effective non-orthogonal multiple-access (NOMA) technique, which ranks one of the most promising candidates for future wireless, because of its outstanding performance. However, most of the existing work prefers low-connectivity SCMA systems, which actually cannot fulfill their priorities for massive connection. The difficulties in designing suitable factor graph matrix are responsible for this situation. In this paper, we propose a design manner of factor graph matrix to realize SCMA with large-scale customers. Quasi-cyclic property with shifting is introduced in SCMA factor graph matrix, based on the rules and restrictions of SCMA design including the column weight and the overloading factor. For numerical analysis, we introduce a performance function to show the effectiveness of our proposed SCMA system, and the results reveal that our work are better than conventional ones.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131791748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646463
Yaxi Liu, W. Huangfu, Haijun Zhang, Keping Long
The power consumption of the base stations is the major part of the total consumption of mobile communications, which implies that it is of great significance to reduce the radio transmit power consumption of base stations under the constraint of quality of service. The dynamic of the traffic leads to the adaptive adjustment of the antenna parameters of the base stations or even turning off some base stations serving low user traffic. We propose a penalty method to convert the power consumption optimization problem which constrained by the coverage condition into a simple form with only lower and upper bound condition. We also transform the discrete-valued coverage index into a continuous one and utilize the sub-gradient to conduct the gradient descent algorithm. Moreover, an elite scheme is adopted to preserve the best solution of the optimization problem. The proposed method is applicable to various optimization conditions, either to adjust the transmit power or to adjust the transmit power and the antenna tilt jointly. Experiment results show that our proposed algorithm performs well in BS ON/OFF switching networks. Besides, the effect of jointly adjusting the antenna tilt and the transmit power is better than that of adjusting the transmit power alone.
{"title":"ELITE GRADIENT DESCENT OPTIMIZATION OF ANTENNA PARAMETERS CONSTRAINED BY RADIO COVERAGE IN GREEN CELLULAR NETWORKS","authors":"Yaxi Liu, W. Huangfu, Haijun Zhang, Keping Long","doi":"10.1109/GlobalSIP.2018.8646463","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646463","url":null,"abstract":"The power consumption of the base stations is the major part of the total consumption of mobile communications, which implies that it is of great significance to reduce the radio transmit power consumption of base stations under the constraint of quality of service. The dynamic of the traffic leads to the adaptive adjustment of the antenna parameters of the base stations or even turning off some base stations serving low user traffic. We propose a penalty method to convert the power consumption optimization problem which constrained by the coverage condition into a simple form with only lower and upper bound condition. We also transform the discrete-valued coverage index into a continuous one and utilize the sub-gradient to conduct the gradient descent algorithm. Moreover, an elite scheme is adopted to preserve the best solution of the optimization problem. The proposed method is applicable to various optimization conditions, either to adjust the transmit power or to adjust the transmit power and the antenna tilt jointly. Experiment results show that our proposed algorithm performs well in BS ON/OFF switching networks. Besides, the effect of jointly adjusting the antenna tilt and the transmit power is better than that of adjusting the transmit power alone.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132793596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646628
Rajesh Amerineni, L. Gupta, Resh S. Gupta
The brain uses contextual information to uniquely resolve the interpretation of ambiguous stimuli. An interdisciplinary effort which combines expertise in machine learning and neuroscience is used to formulate a generalized signal classification model that has the ability to integrate weighted bidirectional temporal or spatial context to effectively resolve the classification of ambiguous stimuli. The formulation of the model is quite general; consequently, it is not restricted to stimuli in any particular sensory modality nor to any type of classifier. Furthermore, the model parameters can be manipulated to simulate various context environments. The context-integrating model is implemented using a Gaussian multivariate classifier and a broad range of experiments are designed to demonstrate its effectiveness in classifying ambiguous visual stimuli in various contextual environments.
{"title":"A CONTEXT-INTEGRATING SIGNAL CLASSIFICATION MODEL FOR RESOLVING AMBIGUOUS STIMULI","authors":"Rajesh Amerineni, L. Gupta, Resh S. Gupta","doi":"10.1109/GlobalSIP.2018.8646628","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646628","url":null,"abstract":"The brain uses contextual information to uniquely resolve the interpretation of ambiguous stimuli. An interdisciplinary effort which combines expertise in machine learning and neuroscience is used to formulate a generalized signal classification model that has the ability to integrate weighted bidirectional temporal or spatial context to effectively resolve the classification of ambiguous stimuli. The formulation of the model is quite general; consequently, it is not restricted to stimuli in any particular sensory modality nor to any type of classifier. Furthermore, the model parameters can be manipulated to simulate various context environments. The context-integrating model is implemented using a Gaussian multivariate classifier and a broad range of experiments are designed to demonstrate its effectiveness in classifying ambiguous visual stimuli in various contextual environments.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130764126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646404
Junyou He, Hailun Xia, Chunyan Feng, Yunfei Chu
Human action recognition has a wide range of applications including biometrics and surveillance. Existing methods mostly focus on a single modality, insufficient to characterize variations among different motions. To address this problem, we present a CNN-based human action recognition framework by fusing depth and skeleton modalities. The proposed Adaptive Multiscale Depth Motion Maps (AM-DMMs) are calculated from depth maps to capture shape, motion cues. Moreover, adaptive temporal windows ensure that AM-DMMs are robust to motion speed variations. A compact and effective method is also proposed to encode the spatio-temporal information of each skeleton sequence into three maps, referred to as Stable Joint Distance Maps (SJDMs) which describe different spatial relationships between the joints. A multi-channel CNN is adopted to exploit the discriminative features from texture color images encoded from AM-DMMs and SJDMs for effective recognition. The proposed method has been evaluated on UTD-MHAD Dataset and achieves the state-of-the-art result.
{"title":"CNN-BASED ACTION RECOGNITION USING ADAPTIVE MULTISCALE DEPTH MOTION MAPS AND STABLE JOINT DISTANCE MAPS","authors":"Junyou He, Hailun Xia, Chunyan Feng, Yunfei Chu","doi":"10.1109/GlobalSIP.2018.8646404","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646404","url":null,"abstract":"Human action recognition has a wide range of applications including biometrics and surveillance. Existing methods mostly focus on a single modality, insufficient to characterize variations among different motions. To address this problem, we present a CNN-based human action recognition framework by fusing depth and skeleton modalities. The proposed Adaptive Multiscale Depth Motion Maps (AM-DMMs) are calculated from depth maps to capture shape, motion cues. Moreover, adaptive temporal windows ensure that AM-DMMs are robust to motion speed variations. A compact and effective method is also proposed to encode the spatio-temporal information of each skeleton sequence into three maps, referred to as Stable Joint Distance Maps (SJDMs) which describe different spatial relationships between the joints. A multi-channel CNN is adopted to exploit the discriminative features from texture color images encoded from AM-DMMs and SJDMs for effective recognition. The proposed method has been evaluated on UTD-MHAD Dataset and achieves the state-of-the-art result.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130977281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GLOBALSIP.2018.8646678
C. Kamath, Y. Fan
Compressing unstructured mesh data from computer simulations poses several challenges that are not encountered in the compression of images or videos. Since the spatial locations of the points are not on a regular grid, as in an image, it is difficult to identify near neighbors of a point whose values can be exploited for compression. In this paper, we investigate how three very different methods — spline fits, compressed sensing, and kernel regression — compare in terms of the reconstruction accuracy and reduction in data size when applied to a practical problem from a plasma physics simulation.
{"title":"COMPRESSING UNSTRUCTURED MESH DATA USING SPLINE FITS, COMPRESSED SENSING, AND REGRESSION METHODS","authors":"C. Kamath, Y. Fan","doi":"10.1109/GLOBALSIP.2018.8646678","DOIUrl":"https://doi.org/10.1109/GLOBALSIP.2018.8646678","url":null,"abstract":"Compressing unstructured mesh data from computer simulations poses several challenges that are not encountered in the compression of images or videos. Since the spatial locations of the points are not on a regular grid, as in an image, it is difficult to identify near neighbors of a point whose values can be exploited for compression. In this paper, we investigate how three very different methods — spline fits, compressed sensing, and kernel regression — compare in terms of the reconstruction accuracy and reduction in data size when applied to a practical problem from a plasma physics simulation.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133310566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646351
M. Vázquez, A. Pérez-Neira
This paper introduces the notion of beam-free satellite systems and it investigates different scheduling algorithms for this architecture. Attending to the current satellite gateway cloudification, this paper assumes that users from different beams can be scheduled over the same frame. Indeed, considering full frequency reuse among beams and on ground precoding, we show that whenever the scheduler is able to freely group users independently of their beam location, large attainable rates are obtained. In addition, we also consider that the gateway is able to select a number of simultaneous transmissions which leads to a substantial sum-rate increase. A scheduling scheme based on spectral clustering is proposed and it shows a higher performance compared to other state-of-the-art alternatives. In addition, our method is able to deal with different user terminal traffic classes. Based on the numerical results obtained considering a close-to-real multibeam satellite pattern, we point out that the current per-beam scheduling process is an inefficient network management for multi-beam satellite systems using precoding.
{"title":"SPECTRAL CLUSTERING FOR BEAM-FREE SATELLITE COMMUNICATIONS","authors":"M. Vázquez, A. Pérez-Neira","doi":"10.1109/GlobalSIP.2018.8646351","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646351","url":null,"abstract":"This paper introduces the notion of beam-free satellite systems and it investigates different scheduling algorithms for this architecture. Attending to the current satellite gateway cloudification, this paper assumes that users from different beams can be scheduled over the same frame. Indeed, considering full frequency reuse among beams and on ground precoding, we show that whenever the scheduler is able to freely group users independently of their beam location, large attainable rates are obtained. In addition, we also consider that the gateway is able to select a number of simultaneous transmissions which leads to a substantial sum-rate increase. A scheduling scheme based on spectral clustering is proposed and it shows a higher performance compared to other state-of-the-art alternatives. In addition, our method is able to deal with different user terminal traffic classes. Based on the numerical results obtained considering a close-to-real multibeam satellite pattern, we point out that the current per-beam scheduling process is an inefficient network management for multi-beam satellite systems using precoding.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115010278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646590
Katherine McLeod, L. Girchenko, Peter Spenler, P. Spachos
Developments in the Internet of Things (IoT) in recent years has allowed for wireless sensor data to be collected and communicated with more ease than ever. This facility of data acquisition has opened possibilities in a large variety of fields, including potential for a significant impact in health care. This paper introduces a framework using IoT sensors to examine correlations between environmental conditions and overall wellness. The proposed system uses a SimpleLink Bluetooth SensorTag and a mobile application to collect environmental data from a subject’s surroundings on a daily basis. The participants also complete daily surveys, which include modified questions from the Pittsburgh Sleep Quality Index (PSQI), the Perceived Stress Scale (PSS), and the Kessler Psychological Distress Scale (K10). Once any correlations between environmental variables and overall wellness have been determined, it should be possible to use this technology to assess and predict one’s wellness using environmental data.
{"title":"A Smartphone-based Wellness Assessment Using Mobile Sensors","authors":"Katherine McLeod, L. Girchenko, Peter Spenler, P. Spachos","doi":"10.1109/GlobalSIP.2018.8646590","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646590","url":null,"abstract":"Developments in the Internet of Things (IoT) in recent years has allowed for wireless sensor data to be collected and communicated with more ease than ever. This facility of data acquisition has opened possibilities in a large variety of fields, including potential for a significant impact in health care. This paper introduces a framework using IoT sensors to examine correlations between environmental conditions and overall wellness. The proposed system uses a SimpleLink Bluetooth SensorTag and a mobile application to collect environmental data from a subject’s surroundings on a daily basis. The participants also complete daily surveys, which include modified questions from the Pittsburgh Sleep Quality Index (PSQI), the Perceived Stress Scale (PSS), and the Kessler Psychological Distress Scale (K10). Once any correlations between environmental variables and overall wellness have been determined, it should be possible to use this technology to assess and predict one’s wellness using environmental data.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124741138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/GlobalSIP.2018.8646392
Keming Cao, Yi Xu, P. Cosman
With the development of augmented reality, the delivery and storage of 3D content have become an important research area. Among the proposals for point cloud compression collected by MPEG, Apple’s Test Model Category 2 (TMC2) achieves the highest quality for 3D sequences under a bitrate constraint. However, the TMC2 framework is not spatially scalable. In this paper, we add interpolation components which make TMC2 suitable for flexible resolution. We apply a patch-aware averaging filter to eliminate most outliers which result from the interpolation. Experimental results show that our method performs well both on objective evaluation and visual quality.
随着增强现实技术的发展，3D内容的传输和存储已成为一个重要的研究领域。在MPEG收集的点云压缩建议中，Apple的Test Model Category 2 (TMC2)在比特率约束下实现了3D序列的最高质量。然而，TMC2框架在空间上是不可扩展的。在本文中，我们增加了插值元件，使TMC2适合灵活的分辨率。我们应用了一个补丁感知的平均滤波器来消除由插值产生的大多数异常值。实验结果表明，该方法在客观评价和视觉质量方面都取得了良好的效果。
{"title":"PATCH-AWARE AVERAGING FILTER FOR SCALING IN POINT CLOUD COMPRESSION","authors":"Keming Cao, Yi Xu, P. Cosman","doi":"10.1109/GlobalSIP.2018.8646392","DOIUrl":"https://doi.org/10.1109/GlobalSIP.2018.8646392","url":null,"abstract":"With the development of augmented reality, the delivery and storage of 3D content have become an important research area. Among the proposals for point cloud compression collected by MPEG, Apple’s Test Model Category 2 (TMC2) achieves the highest quality for 3D sequences under a bitrate constraint. However, the TMC2 framework is not spatially scalable. In this paper, we add interpolation components which make TMC2 suitable for flexible resolution. We apply a patch-aware averaging filter to eliminate most outliers which result from the interpolation. Experimental results show that our method performs well both on objective evaluation and visual quality.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128358353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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