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检索条件"任意字段=Conference on Visual Communications and Image Processing 2007"

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Combining Intra Block Copy and Neighboring Samples Using Convolutional Neural Network for image Coding 33

Combining Intra Block Copy and Neighboring Samples Using Con...

引用

33rd IEEE International conference on visual communications and image processing (IEEE VCIP)

作者： Zhang, Zhaobin Li, Yue Li, Li Li, Zhu Liu, Shan Univ Missouri Dept Comp Sci Elect Engn Kansas City MO 64110 USA Univ Sci & Technol China Dept Elect Engn Informat Sci Hefei Anhui Peoples R China Tencent Amer Media Lab Palo Alto CA USA Univ Missouri Kansas City MO 64110 USA

ISBN: (纸本)9781538644584

Intra prediction is an essential step to remove spatial redundancy in image coding. How to best predict current block given surrounding pixels is the key efficiency challenge. Inspired by the recent success in applying deep learning to image/video coding systems, we propose an intra prediction method by combining intra block copy and neighboring samples using convolutional neural networks. A novel CNN is developed to further exploit the spatial correlation. Instead of only considering local information, the proposed method can infer the current block via fusing the non-local recurrent features, which is captured by intra block copy, with the local samples located at the left and above boundaries of current block. We also investigate how the performance is affected by the way of fusing IBC and reference boundary pixels. In additional, training data pre-processing is studied to enable the CNN with a better learning capability. Simulation results yield promising coding gain and indicate great potential ability that CNN can be used for next generation video coding framework.

关键词： Convolutional neural network (CNN) Intra prediction High Efficiency Video Coding (HEVC) image coding Intra block copy

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An Improved and Optimized Content-Aware Resizing Algorithm for images with Densely Situated Foreground Objects 3

An Improved and Optimized Content-Aware Resizing Algorithm f...

引用

IEEE International conference on Wireless communications, Signal processing and Networking (IEEE WiSPNET)

作者： Roy, Soumyakanti Dasgupta, Tanmoy Pradhan, Tapan Techno India Univ Dept Elect Engn Kolkata W Bengal India

ISBN: (纸本)9781538636244

An image in general consists of a combination of significant objects in the foreground and not-so-significant objects in the background. Content aware image resizing or seam carving is a process of resizing an image while maintaining the significant objects (the foreground) in proper visual saliency. The standard algorithms, however, often generate unpredictable distortions in images with densely situated foreground objects. The optimized content aware image resizing (OCAIR) algorithm presented herein, uses iterative graph cuts and edge detection to generate an energy map based on the important sections of the image, so that the resized image does not exhibit unpredictable artefacts. An improved energy map generation algorithm is designed here, which not only marks out the important foreground elements quicker than previously available techniques, but also uses that information to quantify the amount of distortion (if any) that might take place after adding or deleting seams by means of calculating a distortion factor. The process being considerably faster than previous algorithms, allows precise modifications to the input parameters to obtain a well-doctored final image.

关键词： Content-aware image resizing seam carving GrabCut

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Efficient 3D Liver Segmentation using Enhanced image Alignment

Efficient 3D Liver Segmentation using Enhanced Image Alignme...

引用

conference on Information communications Technology and Society (ICTAS)

作者： Hiraman, Anura Viriri, Serestina Gwetu, Mandlenkosi Univ KwaZulu Natal Sch Math Stat & Comp Sci Durban South Africa

ISBN: (纸本)9781538610015

An efficient and fully automated algorithm for the alignment of serially acquired 2D slices forming a 3D volume is presented. The methodology includes four stages: pre-processing using a median filter, obtaining a threshold value via a Laplacian weighted histogram, skeletonization and image alignment. The introduction of the skeletonization in this approach ensures that the images are being aligned with respect to the bones and large organs. The image alignment algorithm relies on the Enhanced Correlation Coefficient (ECC) alignment algorithm. The presented approach is evaluated on the Medical image Computing and Computer Assisted Intervention (MICCAI) 2007 grand challenge datasets and the evaluation metric used is mean squared difference (MSD). The proposed approach proved to perform well and achieved an improvement in the MSD by an average of 32.85%.

关键词： Liver segmentation Skeletonization image alignment MICCAI 2007 Liver dataset

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Comprehensive Samples Constrain for Person Search 33

Comprehensive Samples Constrain for Person Search

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33rd IEEE International conference on visual communications and image processing (IEEE VCIP)

作者： Li, Liangqi Yang, Hua Chen, Lin Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China Natl Engn Lab Publ Secur Risk Percept & Control B Beijing Peoples R China

ISBN: (纸本)9781538644584

In this paper, we propose a method to further improve person search by fully utilizing the combination of pedestrian detection and person re-identification tasks. An improved constrain that utilizes comprehensive samples in the dataset is proposed to fully excavate information for recognition. Besides the label constrain for training the model in traditional classification task, unlabeled identities that do not have specific IDs are utilized as well to constitute a tailored triplet loss for more performance improvement. Meanwhile, a novel large-scale challenging dataset, SJTU318, which uses videos acquired through twelve cameras is proposed to demonstrate the effectiveness of our method. It contains 443 identities and 14,610 frames in which pedestrians are annotated with their bounding box positions and identities. Experiments conducted on a public dataset, CUHK-SYSU and our proposed dataset SJTU318 show that our method outperforms existing state-of-the-art approaches.

关键词： Pedestrian detection person re-identification person search deep learning triplet loss

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Robust Fabrication of Share to Assure Error Free Dissemination of Secret Data (RFSAEFDSD) 3

Robust Fabrication of Share to Assure Error Free Disseminati...

引用

IEEE International conference on Wireless communications, Signal processing and Networking (IEEE WiSPNET)

作者： Goswami, Anirban Mukherjee, Ritesh Ghoshal, Nabin Techno India EM 4-1Sect 5 Kolkata India Ctr Dev Adv Comp Kolkata India Univ Kalyani Dept Engn & Technol Studies Kalyani W Bengal India

ISBN: (纸本)9781538636244

In wireless domain, digital communication requires effective data security. The proposed algorithm promotes effective security by incorporating visual cryptography, sharing of secret data through robust fabrication, error identification & correction using the binary repetition code of length 3 and authentication of the secret data through Hash value checking. The effective utilization of two distinct color cover images and the three planes simultaneously justifies robustness in hiding. In addition, the use of mid frequency region of DCT spectrum and pseudorandom casting locations support resistance to some other image processing attacks apart from JPEG compression. The volume of payload is increased considerably by fabricating four bits at a time in a single block. The data correctness is well supported by reducing the computational overhead and introducing error bit correction. At the receiving end, the authorization of a document and its owner is ratified by a Hash function. The experimentation of the algorithm and subsequent analysis of the results depict the credibility of the algorithm in the domain of data security.

关键词： visual Cryptography image compression Binary repetition code Data fabrication Bit error correction NCC SSIM

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Driving Maneuvers Prediction Based on Cognition-driven and Data-driven Method 33

Driving Maneuvers Prediction Based on Cognition-driven and D...

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33rd IEEE International conference on visual communications and image processing (IEEE VCIP)

作者： Zhou, Dong Ma, Huimin Dong, Yuhan Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781538644584

Advanced Driver Assistance Systems (ADAS) improve driving safety significantly. They alert drivers from unsafe traffic conditions when a dangerous maneuver appears. Traditional methods to predict driving maneuvers are mostly based on data-driven models alone. However, existing methods to understand the driver's intention remain an ongoing challenge due to a lack of intersection of human cognition and data analysis. To overcome this challenge, we propose a novel method that combines both the cognition-driven model and the data-driven model. We introduce a model named Cognitive Fusion-RNN (CF-RNN) which fuses the data inside the vehicle and the data outside the vehicle in a cognitive way. The CF-RNN model consists of two Long Short-Term Memory (LSTM) branches regulated by human reaction time. Experiments on the Brain4Cars benchmark dataset demonstrate that the proposed method outperforms previous methods and achieves state-of-the-art performance.

关键词： image cognition data fusion ADAS Recurrent neural networks driving maneuvers prediction CF-RNN

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Siamese Network for visual Tracking via Focal Loss

Siamese Network for Visual Tracking via Focal Loss

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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： Shan Jiang Cheng Han Xiaoqiang Di Hua Li School of Computer Science and Technology ChangChun Unviersity of Science and Technology Changchun China

ISBN: (纸本)9781728152103

visual tracking is a fundamental problem in computer vision. Lots efforts have been made in the past decades and researchers have obtained some achievements, but there are still problems exist. To get a more powerful feature representation, deep learning based methods appear layer upon layer, and most of them achieve good performance at the price of losing speed. In this paper, we propose a SiamFL network for visual tracking, which introduce the focal loss with the Siamese network. With the focal loss, the network is capable of filtering out the easy examples, leaving the hard samples to train a discriminative network. Moreover, the SiamFL network also can alleviate the class imbalance problem by properly sampling the positive and negative samples at a certain ratio. Experimental results demonstrate the SimaFL has quick convergence and also have a better performance over the baseline tracker.

关键词： computer vision image representation learning (artificial intelligence) visual tracking image representation images computer vision siamese Balance impairment Network

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Automated Coronary Tree Segmentation for X-ray Angiography Sequences Using Fully-convolutional Neural Networks 33

Automated Coronary Tree Segmentation for X-ray Angiography S...

引用

33rd IEEE International conference on visual communications and image processing (IEEE VCIP)

作者： Zhao, Lei Li, Deyu Chen, Jianhui Wan, Tao Beihang Univ Sch BSME Beijing Peoples R China 91 Cent Hosp PLA Jiaozuo Henan Peoples R China Beihang Univ Beijing Adv Innovat Ctr Biomed Engn Beijing Peoples R China

ISBN: (纸本)9781538644584

Cardiovascular disease is the number one killer that threatens human health. Analysis of coronary vascular geometry plays an important role in the diagnosis of cardiovascular disease. In order to make reliable judgments for clinical usage, accurate and robust vascular segmentation methods are needed. We present an improved segmentation approach for dynamic coronary angiography sequences, which can obtain blood vessel trees in real time. We start with a pre-trained convolutional neural network (CNN) on imageNet as the base network for initialization. We then adapt this network to the structure of one-shot video object segmentation (OSVOS) to obtain the parent network, which is trained on 50 X-ray angiography sequences for extracting blood vessels. Finally, the model is further fine-tuned using 10 specific coronary angiography sequences to achieve real-time vascular segmentation. Our method achieved the Dice index of 0.88, suggesting that the presented method can be potentially useful in developing a real-time segmentation method for coronary angiography sequences.

关键词： coronary tree extraction dynamic image segmentation coronary angiography convolutional neural networks

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Virtual View Quality Enhancement Using Side View Information for Free Viewpoint Video 33

Virtual View Quality Enhancement Using Side View Information...

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33rd IEEE International conference on visual communications and image processing (IEEE VCIP)

作者： Rahaman, D. M. Motiur Paul, Manoranjan Shoumy, Nusrat Jahan Charles Sturt Univ Sch Comp & Math Bathurst NSW Australia

ISBN: (纸本)9781538644584

With the advancement of displaying technologies, virtual viewpoint video needs to be synthesized from adjacent viewpoints to provide immersive perceptual viewing experience of a scene. View synthesized techniques suffer poor rendering quality due to holes created by occlusion in the warping process. Currently, spatial and temporal correlation techniques are used to improve the quality of the synthesized view. However, spatial correlation e. g. inpainting and inverse mapping (IM) techniques cannot fill holes efficiently due to low spatial correlation in the edge between foreground and background pixels. On the other hand, the temporal correlation among already synthesized frames through learning by Gaussian mixture modelling (GMM) may fill occluded areas efficiently. However, there are no frames for GMM learning when the user switches view instantly. To address the aforementioned issues, in the proposed view synthesis technique, we apply GMM on the adjacent viewpoint videos. Then, we utilize the number of GMM models to refine pixel intensities of the synthesized view by using a weighting factor between pixel intensities in GMM models and warped images. This technique provides a better pixel correspondence, which improves 0.47-0.58dB PSNR compared to the IM technique.

关键词： Occlusion depth image-based rendering spatial temporal correlation Gaussian mixture modelling inverse mapping

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Improving visual presentation of bas relief image from historical temple 1

Improving visual presentation of bas relief image from histo...

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1st International conference on Information and communications Technology, ICOIACT 2018

作者： Auliasari, Karina Orisa, Mira Malang Indonesia

ISBN: (纸本)9781538609545

Two stages are developed in this research namely optimal pre-processing and main-processing. The pre-processing is to enhance the presentation of image relief by using contrast stretching, histogram equalization and adaptive histogram equalization. Here the presentation of image is vital for the input of main process. Three operations of image enhancement are employed to improve image contrast, including contrast stretching, histogram equalization and adaptive histogram equalization. Comparison between contrast stretching with a value 1.1 and histogram equalization show that the gray-level of histogram equalization result are distributed. Experiment of show that the adaptive histogram equalization has produced the best image enhancement. After doing image enhancement the next step is to do threshold and edge detection operations. This procedure enhances horizontal or vertical edge of the figure. The image enhancement operation is very useful to remove the illumination no uniformities. Threshold process using Otsu algorithm shows that both of LPF kernel 1 and 2 output image have a similar result rather than LPF kernel 3. Three of LPF kernels has produced two different threshold values. Kapur algorithm show that both of LPF kernel 2 dan 3 output image have a similar result of rather than LPF kernel 1 output image. The experiment also show that Sobel and Canny operators has enhanced edges and weaken weak textures. © 2018 IEEE.

关键词： image enhancement

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