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

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MPEG Immersive Video tools for Light Field Head Mounted Displays

MPEG Immersive Video tools for Light Field Head Mounted Disp...

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IEEE visual communications and image processing (VCIP)

作者： Daniele Bonatto Grégoire Hirt Alexander Kvasov Sarah Fachada Gauthier Lafruit Laboratories of Image Synthesis and Analysis Université Libre de Bruxelles Brussels Belgium CREAL Lausanne Switzerland

ISBN: (纸本)9781728173221

Light field displays project hundreds of micro-parallax views for users to perceive 3D without wearing glasses. It results in gigantic bandwidth requirements if all views would be transmitted, even using conventional video compression per view. MPEG Immersive Video (MIV) follows a smarter strategy by transmitting only key images and some metadata to synthesize all the missing views. We developed (and will demonstrate) a real-time Depth image Based Rendering software that follows this approach for synthesizing all light field micro-parallax views from a couple of RGBD input views.

关键词： Three-dimensional displays visual communication Transform coding Streaming media Video compression Metadata Rendering (computer graphics)

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International conference on communications, Signal processing and VLSI, IC2SV 2019

International Conference on Communications, Signal Processin...

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International conference on communications, Signal processing and VLSI, IC2SV 2019

ISBN: (纸本)9789813340572

The proceedings contain 36 papers. The special focus in this conference is on communications, Signal processing and VLSI. The topics include: Design and Analysis of Wearable Step-Shaped Sierpinski Fractal Antenna for WBAN Applications;Evaluation of Real-Time Embedded Systems in HILS and Delay Issues;acoustic Feedback Cancellation Using Optimal Step-Size Control of the Partition Block Frequency-Domain Adaptive Filter;A Compact IPD Based on-Chip Bandpass Filter for 5G Radio Applications;An 18-Bit Incremental Zoom ADC with Reduced Delay Overhead Data Weighted Averaging for Battery Measurement Systems;a Non-Uniform Digital Filter Bank Hearing Aid for Aged People with Hearing Disability;optimal Resource Allocation Based on Particle Swarm Optimization;Design and Simulation of a W-Band FMCW Radar for Cloud Profiling Application;Single Layer Asymmetric Slit Circularly Polarized Patch Antenna for WLAN Application;recognition of Natural and Computer-Generated images Using Convolutional Neural Network;contour and Texture-Based Approaches for Dental Radiographic and Photographic images in Forensic Identification;an Efficient Low Latency Router Architecture for Mesh-Based NoC;high-Performance image visual Feature Detection and Matching;systolic-Architecture-Based Matrix Multiplications and Its Realization for Multi-Sensor Bias Estimation Algorithms;fast Encoding Using X-Search Pattern and Coded Block Flag Fast Method;Energy Efficient and Accurate Hybrid CSA-CIA Adders;machine Learning Oriented Dynamic Cost Factors-Based Routing in Communication Networks;Design of Look-Up Table with Low Leakage Power Enhanced Stability 10 T SRAM Cell;Conformal Omni Directional Antenna for GPS Applications;total Internal Reflection Quasi-Phase-Matching-Based Broadband Second Harmonic Generation in Isotropic Semiconductor: A Comparative Analysis;automated Bayesian Drowsiness Detection System Using Recurrent Convolutional Neural Networks.

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Spatio-spectral image Reconstruction Using Non-local Filtering

Spatio-spectral Image Reconstruction Using Non-local Filteri...

引用

IEEE visual communications and image processing (VCIP)

作者： Frank Sippel Jürgen Seiler André Kaup Multimedia Communications and Signal Processing Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany

ISBN: (纸本)9781728173221

In many image processing tasks it occurs that pixels or blocks of pixels are missing or lost in only some channels. For example during defective transmissions of RGB images, it may happen that one or more blocks in one color channel are lost. Nearly all modern applications in image processing and transmission use at least three color channels, some of the applications employ even more bands, for example in the infrared and ultraviolet area of the light spectrum. Typically, only some pixels and blocks in a subset of color channels are distorted. Thus, other channels can be used to reconstruct the missing pixels, which is called spatio-spectral reconstruction. Current state-of-the-art methods purely rely on the local neighborhood, which works well for homogeneous regions. However, in high-frequency regions like edges or textures, these methods fail to properly model the relationship between color bands. Hence, this paper introduces non-local filtering for building a linear regression model that describes the inter-band relationship and is used to reconstruct the missing pixels. Our novel method is able to increase the PSNR on average by 2 dB and yields visually much more appealing images in high-frequency regions.

关键词： image color analysis Filtering visual communication image edge detection Linear regression Buildings Reconstruction algorithms

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DFTS2: Deep Feature Transmission Simulation for Collaborative Intelligence

DFTS2: Deep Feature Transmission Simulation for Collaborativ...

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IEEE visual communications and image processing (VCIP)

作者： Ashiv Dhondea Robert A. Cohen Ivan V. Bajić School of Engineering Science Simon Fraser University Burnaby BC Canada

ISBN: (纸本)9781728173221

In edge-cloud collaborative intelligence (CI), an unreliable transmission channel exists in the information path of the AI model performing the inference. It is important to be able to simulate the performance of the CI system across an imperfect channel in order to understand system behavior and develop appropriate error control strategies. In this paper we present a simulation framework called DFTS2, which enables researchers to define the components of the CI system in TensorFlow 2, select a packet-based channel model with various parameters, and simulate system behavior under various channel conditions and error/loss control strategies. Using DFTS2, we also present the most comprehensive study to date of the packet loss concealment methods for collaborative image classification models.

关键词： image coding Monte Carlo methods visual communication Neural networks Packet loss Collaboration Propagation losses

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Video Coding Pre-processing Based on Rate-Distortion Optimized Weighted Guided Filter

Video Coding Pre-Processing Based on Rate-Distortion Optimiz...

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IEEE visual communications and image processing (VCIP)

作者： Xi Huang Luheng Jia Han Wang Kebin Jia Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781728173221

In video coding, it is always an intractable problem to compress high frequency components including noise and visually imperceptible content that consumes large amount bandwidth resources while providing limited quality improvement. Direct using of denoising methods causes coding performance degradation, and hence not suitable for video coding scenario. In this work, we propose a video pre-processing approach by leveraging edge preserving filter specifically designed for video coding, of which filter parameters are optimized in the sense of rate-distortion (R-D) performance. The proposed pre-processing method removes low R-D cost-effective components for video encoder while keeping important structural components, leading to higher coding efficiency and also better subjective quality. Comparing with the conventional denoising filters, our proposed pre-processing method using the R-D optimized edge preserving filter can improve the coding efficiency by up to −5.2% BD-rate with low computational complexity.

关键词： Video coding Degradation image coding image resolution visual communication Noise reduction Rate-distortion

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Quaternion-driven CNN for Object Pose Tracking

Quaternion-driven CNN for Object Pose Tracking

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IEEE visual communications and image processing (VCIP)

作者： Mateusz Majcher Bogdan Kwolek AGH University of Science and Technology Kraków Poland

ISBN: (纸本)9781728173221

In this work we propose a new mixed-input neural network for instance level monocular object tracking. The proposed Y-like architecture has two inputs and one output. An object id with a quaternion representing the object rotation in the previous frame are fed to the first input, whereas the object sub-window is fed to the second input. We demonstrate that on the basis of quaternions the neural network learns attention blobs representing the object rotation in the previous frame. A single neural network has been trained for six objects to estimate their fiducial points in sequences of RGB images. A tracking by optimization approach has been leveraged in the experiments. The algorithm has been evaluated on the OPT benchmark dataset for 6DoF object pose tracking as well as a custom dataset including image sequences with both real and rendered objects.

关键词： visual communication Quaternions Neural networks Pose estimation Optimized production technology Benchmark testing image sequences

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Aerial image Classification with Label Splitting and Optimized Triplet Loss Learning

Aerial Image Classification with Label Splitting and Optimiz...

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IEEE visual communications and image processing (VCIP)

作者： Rijun Liao Zhu Li Shuvra S. Bhattacharyya George York University of Missouri-Kansas City MO USA University of Maryland College Park MD USA US Air Force Academy UAS Research Center Colorado Springs CO USA

ISBN: (纸本)9781728173221

With the development of airplane platforms, aerial image classification plays an important role in a wide range of remote sensing applications. The number of most of aerial image dataset is very limited compared with other computer vision datasets. Unlike many works that use data augmentation to solve this problem, we adopt a novel strategy, called, label splitting, to deal with limited samples. Specifically, each sample has its original semantic label, we assign a new appearance label via unsupervised clustering for each sample by label splitting. Then an optimized triplet loss learning is applied to distill domain specific knowledge. This is achieved through a binary tree forest partitioning and triplets selection and optimization scheme that controls the triplet quality. Simulation results on NWPU, UCM and AID datasets demonstrate that proposed solution achieves the state-of-the-art performance in the aerial image classification.

关键词： Training Histograms visual communication Simulation image processing Semantics Forestry

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SDE-DualENet: A Novel Dual Efficient Convolutional Neural Network for Robust Stereo Depth Estimation

SDE-DualENet: A Novel Dual Efficient Convolutional Neural Ne...

引用

IEEE visual communications and image processing (VCIP)

作者： Rithvik Anil Mansi Sharma Rohit Choudhary Mechanical Engineering IIT Madras Electrical Engineering IIT Madras

ISBN: (纸本)9781728173221

Stereo depth estimation is dependent on optimal correspondence matching between pixels of stereo-pair image to infer depth. In this paper, we attempt to revisit the stereo depth estimation problem in a simple dual convolutional neural network (CNN) based on EfficientNet that avoids the construction of a cost volume in stereo matching. This has been performed by considering different weights in otherwise identical towers of the CNN. The proposed algorithm is dubbed as SDE-DualENet. The architecture of SDE-DualENet eliminates the construction of cost-volume by learning to match correspondence between pixels with a different set of weights in the dual towers. The results are demonstrated on complex scenes with high details and large depth variations. The SDE-DualENet depth prediction network outperforms state-of-the-art monocular and stereo depth estimation methods, both qualitatively and quantitatively on challenging scene flow dataset. The code and pre-trained models will be made publicly available.

关键词： Costs Codes visual communication image processing Poles and towers Estimation Prediction algorithms

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Cross-Component Sample Offset for image and Video Coding

Cross-Component Sample Offset for Image and Video Coding

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IEEE visual communications and image processing (VCIP)

作者： Yixin Du Xin Zhao Shan Liu Tencent America Palo AltoCAUnited States94306

ISBN: (纸本)9781728173221

Existing cross-component video coding technologies have shown great potential on improving coding efficiency. The fundamental insight of cross-component coding technology is respecting the statistical correlations among different color components. In this paper, a Cross-Component Sample Offset (CCSO) approach for image and video coding is proposed inspired by the observation that, luma component tends to contain more texture, while chroma component is relatively smoother. The key component of CCSO is a non-linear offset mapping mechanism implemented as a look-up-table (LUT). The input of the mapping is the co-located reconstructed samples of luma component, and the output is offset values applied on chroma component. The proposed method has been implemented on top of a recent version of libaom. Experimental results show that the proposed approach brings 1.16% Random Access (RA) BD-rate saving on top of AV1 with marginal encoding/decoding time increase.

关键词： Video coding image coding Correlation visual communication image color analysis Filtering Simulation

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Adaptive Threshold-based Sparse Representation Network for image Compressive Sensing Reconstruction

Adaptive Threshold-based Sparse Representation Network for I...

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IEEE visual communications and image processing (VCIP)

作者： Yunyi Xuan Chunling Yang Xin Yang School of Electronic and Information Engineering South China University of Technology

ISBN: (纸本)9781728173221

Recently, network-based image Compressive Sensing (ICS) algorithms show superior performance in reconstruction quality and speed, yet non-interpretable. Herein, we propose an Adaptive Threshold-based Sparse Representation Reconstruction Network (ATSR-Net), composed of the Convolutional Sparse Representation subnet (CSR-subnet) and the truly Adaptive Threshold Generation subnet (ATG-subnet). The traditional iterations are unfolded into several CSR-subnets, which can fully exploit the local and nonlocal similarities. The ATG-subnet automatically determines a threshold map based on the image intrinsic characterization for flexible feature selection. Moreover, we present a three-level consistency loss based on pixel-level, measurement-level, and feature-level, to accelerate the network convergence. Extensive experiment results demonstrate the superiority of the proposed network to the existing state-of-the-art methods by large margins, both quantitatively and qualitatively.

关键词： Integrated circuits Adaptive systems image coding visual communication Machine learning Loss measurement Sensors

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