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Collar Data Synthesis and Its Application for Generating Virtual Collar 3D Novel View from a Single-View

Collar Data Synthesis and Its Application for Generating Vir...

引用

IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Na Guo Pei-Wei Tsai Hongwang Xiao Chang Wu Wenjuan Duan Department of Computing Technologies Swinburne University of Technology Melbourne Australia School of Mechanical Electrical &Information Engineering Shandong University Weihai Weihai China Beijing Academy Artificial Intelligence Beijing China Department of Computing Technologies Beijing Institute of Technology Beijing China

In recent years, virtual reality, big data and cloud computing technologies have all made rapid development, and they are also more and more closely combined with the apparel industry. The apparel digital design and virtual fitting techniques are playing increasingly important roles in the field of apparel design, manufacturing and sales. The three-dimensional digital design and virtual fitting make the designers or the users have multi-view and more real impressions and experiences of the apparel. But 3D display is difficult to be popularized in apparel industry because of its high cost. The cost of two-dimensional display is low and easy to popularize. However, 2D system can only provide images of a specific perspective, lacking a multi-perspective experience. If the supplier is required to provide 2D images of several specific perspectives, the personalized needs of users cannot be satisfied. Therefore, how to make 2D system according to an object image and users' needs to provide the object images of other perspectives is an urgent problem to be solved. In this work, we propose a novel view synthesis pipeline based on an enhanced Pix2Pix neural network for a novel view (Pix2Pix-V). It consists of four parts: 1) a new method of generating the labeled virtual collar image data based on its 3D model, and the 2D images can be obtained on any perspective; 2) Pix2Pix-V neural network; 3) a Pix2Pix-V training workflow for predicting the novel view; 4) transfer learning is used in predicting similar views of virtual collars.

关键词： Industries Solid modeling Three-dimensional displays Costs Pipelines Transfer learning Neural networks

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Image capture using integrated 3D SoftChip technology

Image capture using integrated 3D SoftChip technology

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IEEE international conference on High Speed Networks and Multimedia Communications

作者： S. Lachowicz A. Rassau G. Alagoda K. Eshraghian M.M.-O. Lee Seung-Min Lee Centre for Very High Speed Microelectronic Systems Edith Cowan University Joondalup WA Australia School of EE Information and Communication Eng. Dongshin University Naju Chonnam Korea

Mobile multimedia communication has rapidly become a significant area of research and development. The processing requirements for the capture, conversion, compression, decompression, enhancement, display, etc. of high quality multimedia content places heavy demands even on current ULSI (ultra large scale integration) systems, particularly for mobile applications where area and power are primary considerations. The system presented is designed as a vertically integrated (3D) system comprising two distinct layers bonded together using indium bump technology. The top layer is a CMOS imaging array containing analog-to-digital converters, and a buffer memory. The bottom layer takes the form of a configurable array processor (CAP), a highly parallel array of soft programmable processors capable of carrying out complex processing tasks directly on data stored in the top plane. Until recently, the dominant format of data in imaging devices has been analog. The analog photocurrent or sampled voltage is transferred to the ADC via a column or a column/row bus. In the proposed system, an array of analog-to-digital converters is distributed, so that a one-bit cell is associated with one sensor. The analog-to-digital converters are algorithmic current-mode converters. Eight such cells are cascaded to form an 8-bit converter. Additionally, each photosensor is equipped with a current memory cell, and multiple conversions are performed with scaled values of the photocurrent for colour processing.

关键词： Analog-digital conversion Sensor arrays Ultra large scale integration Photoconductivity Multimedia communication Mobile communication Research and development Image converters Image coding Displays

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An RFID-Based distributed control system for mass customization manufacturing 04

引用

Proceedings of the Second international conference on parallel and distributed processing and applications

作者： Michael R. Liu Q. L. Zhang Lionel M. Ni Mitchell M. Tseng Department of Computer Science Hong Kong University of Science and Technology Kowloon Hong Kong Department of Industrial Engineering & Engineering Management Hong Kong University of Science and Technology Kowloon Hong Kong

ISBN: (纸本)9783540241287

Mass customization production means to produce customized products to meet individual customer's need with the efficiency of mass production. It introduces challenges such as drastic increase of varieties, very small batch size and random arrival of orders, thus brings to the manufacturing control system requirements of flexibility and responsiveness which make mass customization production a fertile ground for intelligent agents. With RFID (Radio Frequency Identification) integration, an applicable agent-based heterogeneous coordination mechanism is developed to fulfill the requirements. In this paper, we propose a distributed system framework including a number of intelligent agents to collaborate in a virtual market-like environment. The proposed price mechanism in our system has the advantage of improving the production efficiency and total profit that the manufacturer will receive from a certain amount of jobs by utilizing a mechanism of both resource competition and job competition. Based on the simulation results, we compare the total profit, average delay and average waiting time of our agent-based price mechanism with those based on the widely exploit FIFO (First In First Out) and EDD (Earliest Due Date) scheduling mechanisms to show that when resources are with large queue length, the agent-based price mechanism significantly outperforms the other two.

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Research on 3D CAD Model Retrieval Algorithm Based on Global and Local Similarity

Research on 3D CAD Model Retrieval Algorithm Based on Global...

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IEEE international Symposium on parallel and distributed processing with applications and IEEE international conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Weifang Ma Peiyan Wang Dongfeng Cai Dahan Wang Human-computer Intelligence Research Center Shenyang Aerospace University Shenyang People’s Republic of China

ISBN: (纸本)9781728152103

Content-based 3D CAD model retrieval takes a 3D CAD model as input and finds other models with the same or similar structure. This paper proposes a two-stage retrieval method that can take into account the global and local similarity of CAD models. In the first stage, the CAD model formation candidate modles with high global matching degree with the query model is selected, and the TF-IMF (Term Frequency-Inverse Model Frequency) vector method is proposed to describe the global surface line distribution of the 3D CAD model. In the second stage, on the basis of the global similarity, the models which are locally similar with the query models are further filtered, and the attribute adjacency graphs between models are calculated by ACO (ant colony optimization) algorithm. Experimental results show that the proposed method achieves better retrieval performance than the maximum clique method based on the attribute adjacency graph (NDCG), which is 90.68%, and has higher retrieval efficiency.

关键词： ant colony optimisation CAD content-based retrieval design feature extraction graph theory image matching image retrieval solid modelling entity modeling Computer-Aided Design DFFB gene Content retrieval image matching image retrieval Graph theory Feature extraction Ant colony optimization retrieval three-dimensional displays

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GeoKSGrid:A geographical knowledge grid with functions of spatial data mining and spatial decision

GeoKSGrid:A geographical knowledge grid with functions of sp...

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2011 IEEE international conference on Spatial Data Mining and Geographical Knowledge Services(ICSDM 2011)

作者： Jiaxiang Lin~1,Chongcheng Chen~2,Xiaozhu Wu~3,Jianwei Wu~4,Weibin Wang~5 Spatial Information Research Center of Fujian,Fuzhou University, F13,Science Building,No.523 Gongye Road,Fuzhou 350002,China

Motivated by the lack of a geographical problem solving environment that is adequate to provide end users with reliable,open,distributed,and long lasting spatial data analyzing and knowledge discovery services,a novel geographical knowledge service platform - GeoKSGrid with functions of spatial decision support and distributed & parallel data mining is described in this *** basic concepts and state-of-the-art knowledge in grid research is discussed ***,the design of system architecture and the implementation of several most important modules of GeoKSGrid are ***,some demonstrative applications of the geographical knowledge services in real industry contexts is examined,combining with a brief interpretation of the processing results which confirm the practical value of the services and knowledge grid platform.

关键词： GeoKSGrid knowledge grid spatial data mining spatial decision support geographical problem

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An Integrative Approach to Robust Hand Detection Using CPM-YOLOv3 and RGBD Camera in Real Time

An Integrative Approach to Robust Hand Detection Using CPM-Y...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Muhammad Raza Vachiraporn Ketsoi Haopeng Chen School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Innovative methods to interact with electronic devices are attracting researchers attentions, and many applications of Human Computer Interaction have been developed in recent years. Hand detection under different illuminations and backgrounds is crucial for tasks such as, actions recognition, gestures recognition and hand-based interaction with wearable devices. Many existing methods are able to detect the human hand precisely, but the task still remains challenging due to environment complexity, different invariants, processing time, and accuracy. It is required for an application to recognize the human hand precisely for proper interaction with the wearable devices. This paper proposed a robust and a compact method for hand detection by employing you only look once (YOLO) and convolutional pos machines (CPM). This paper consists of two parts, network training and testing. In the first part, Oxford hand dataset is used to train a neural network. This dataset has various hand images under different invariants, and backgrounds. Afterwards, images are captured using a digital camera in real-time and then human hands are detected using a trained neural network. In addition, detected hands, positions and orientations are calculated accordance with defined active zone parameters and a depth sensor. Our trained neural network is dubbed as HHDNet, an abbreviation for human hand detection network. The HHDNet is tested under different environment conditions, and experimental results showed that the accuracy and the frame rate of the proposed model are superior than others state of the art methods.

关键词： Image color analysis Neural networks Feature extraction Cameras Robot sensing systems Estimation Skin

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High-speed Inter-IC Interfacing for Mobile Multimedia applications

High-speed Inter-IC Interfacing for Mobile Multimedia Applic...

引用

2007 international conference on Consumer Electronics (ICCE 2007)

作者： Aliaksei Sedzin Julien Aguilar Aavid Marechal Richard O'Connor Eric Bernasconi NXP Semiconductors Eindhoven The Netherlands

distributed processing in today's mobile multimedia devices requires efficient ways of inter-IC communication. This paper presents a hardware block allowing the host IC to have parallel asynchronous access to the resources of the target IC. The block targets mobile multimedia applications. It is composed of an asynchronous logic subsystem, configuration registers, a packer, 4 command/data FIFOs, 3 packer FIFOs, 8 Device Transaction Level (DTL) masters and a DTL slave. The block allows the target IC to be directly connected to a memory controller. The block supports 2D transfers, which improves performance and saves power for mobile video applications.

关键词： distributed processing Mobile multimedia Inter IC communication

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Image Matching Algorithm Based on GMS

Image Matching Algorithm Based on GMS

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IEEE international Symposium on parallel and distributed processing with applications and IEEE international conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Hua Li Wen Liu Cheng Han Xiangxu Kong School of Computer Science and Technology Changchun University of Science and Technology Changchun China Changchun University of Science and Technology Changchun China

ISBN: (纸本)9781728152103

Image matching is a technique for measuring the similarity of two or more images to determine the correspondence between images. It is the main research content in the field of computer vision. In order to solve the problem of low matching accuracy of Grid-based Motion Statistics(GMS) algorithm in complex situations such as illumination changes, rotation changes or scale changes, an improved GMS image matching algorithm is proposed. Firstly, we use AKAZE to detect and describe the feature points. Then, the bi-directional KNN matching algorithm is adopted for rough matching. Finally, the GMS algorithm is used to filter and eliminate the false matching point pairs. In order to verify the effectiveness of the proposed method, the Oxford standard datasets and practical images are experimented. The experimental results show that the correct matching rate of the proposed algorithm can reach to 90%. Our method can match better in complex scenes than ORB, and GMS algorithms. In terms of matching time, the proposed method reduces about 15% than original GMS.

关键词： computer vision feature extraction image matching image motion analysis nearest neighbour methods image matching images computer vision image motion analysis Feature extraction nearest neighbor algorithm algorithms Object Request Broker PPP1R3A gene

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Single Image Super-Resolution Reconstruction of Enhanced Loss Function with Multi-GPU Training

Single Image Super-Resolution Reconstruction of Enhanced Los...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Jianqiang Huang Kai Li Xiaoying Wang Department of Computer Technology and Application Qinghai University China Department of Computer Science and Technology Tsinghua University China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

According to research on super-resolution (SR), SR image reconstruction using generated anti-networks can produce images that are more realistic than using convolutional neural networks. At present, SR technology based on convolutional neural networks ignores the impact of loss function on image reconstruction; the results lack detail and accuracy. In this paper, we use SR method and combine Generative Adversarial Networks to design a super-resolution (Lapras-GAN) model of the enhanced loss function. The proposed enhancement loss function is a Mix loss function that combines the multiscale SSIM and L1 loss functions to obtain realistic images. We performed qualitative and quantitative analysis of the performance of different loss functions and demonstrated the advantages of the Mix loss function. In addition, the neural network is accelerated by multiple GPUs of multiple nodes, which can be 3-4 times faster than a single node single GPU. Experimental results show that the proposed Lapras-GAN method can generate images consistent with images produced by human perception. Further comparisons show that our Lapras-GAN has excellent performance and test time in the PIRM2018 experimental test data set. Finally, we obtained a perception index of 1.83 and a test time of 0.031s in the PIRM2018 competition test set.

关键词： Training Gallium nitride Graphics processing units Mathematical model Neural networks Deep learning Image reconstruction

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Hand Motion Based Human Computer Interaction Using 3D Convolutional Neural Network

Hand Motion Based Human Computer Interaction Using 3D Convol...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Vachiraporn Ketsoi Muhammad Raza Haopeng Chen School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Electronic devices have achieved smart functionality due to the emergence of action recognition. More specifically, hand motions classification is one of the main research areas among computer vision research communities, which have tremendous potential in the field of human computer interaction. However, there are various challenges related to the computational cost of this approach. In this paper, a compact method is proposed to recognize hand actions by utilizing 3D convolutional neural network. Without using multiple sensors, our method is merely based on a mono camera. A network is trained using multiple videos of human hand motions, and then an image sequence is forward to the trained neural network for recognizing the corresponding action. Our trained neural network is dubbed as HMRNet, an abbreviation for hand motions recognition network. The HMRNet is trained and tested using 20BN Jester dataset, and experimental results showed that both the estimated error and the accuracy of the proposed network are superior compare to other traditional methods including sensors and features based. The computational efficiency and logical steps of our approach are straightforward that any user interface-based device equipped with a camera and proper hardware can adapt this method. This method allows users to interact with the personal computers in a very interactive and futuristic way, and has the potential to eliminate the use of input devices including mouse and touch pen.

关键词： Sensors Three-dimensional displays Feature extraction Kernel Visualization Gesture recognition Convolutional neural networks

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