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

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Quality-Constant Per-Shot Encoding by Two-Pass Learning-based Rate Factor Prediction

Quality-Constant Per-Shot Encoding by Two-Pass Learning-base...

引用

IEEE International conference on Visual communications and image processing (VCIP)

作者： Cai, Chunlei Wang, Yi Li, Xiaobo Ye, Tianxiao Bilibili Inc Shanghai Peoples R China

ISBN: (纸本)9781665475921

Providing quality-constant streams can simultaneously guarantee user experience and prevent wasting bit-rate. In this paper, we propose a novel deep learning based two-pass encoder parameter prediction framework to decide rate factor (RF), with which encoder can output streams with constant quality. In first-pass, an RF is predicted based on spatial-temporal and pre-coding features of video segment. Then video segment is encoded using the predicted RF and then its VMAF is measured. If first pass VMAF doesn't meet target quality, a second pass prediction is performed using another model, in where results of first pass is added to features. Experiments show the proposed method requires only 1.55 times encoding complexity on average, meanwhile the accuracy, that the compressed video's actual VMAF is within +/- 1 around the target VMAF, reaches 98.88%. Compared with average rate mode, this method can both improve visual quality and save similar to 10% bit-rate, as shown in demos(1).

关键词： video Encoding Quality-Constant Deep Learning Per-Shot Encoding VMAF

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Energy-Efficient video Streaming: A Study on Bit Depth and Color Subsampling

Energy-Efficient Video Streaming: A Study on Bit Depth and C...

引用

2024 conference on Visual communications and image processing

作者： Amirpour, Hadi Qu, Lingfeng Ko, Jong Hwan Stejerean, Cosmin Timmerer, Christian Alpen Adria Univ Christian Doppler Lab ATHENA Klagenfurt Austria Guangzhou Univ Cyberspace Inst Adv Technol Guangzhou Peoples R China Sungkyunkwan Univ Dept Elect & Comp Engn Seoul South Korea Meta Platforms Inc Menlo Pk CA USA

ISBN: (纸本)9798331529543;9798331529550

As video dimensions - including resolution, frame rate, and bit depth - increase, a larger bitrate is required to maintain a higher Quality of Experience (QoE). While videos are often optimized for resolution and frame rate to improve compression and energy efficiency, the impact of color space is often overlooked. Larger color spaces are essential for avoiding color banding and delivering High Dynamic Range (HDR) content with richer, more accurate colors, although this comes at the cost of higher processing energy. This paper investigates the effects of bit depth and color subsampling on video compression efficiency and energy consumption. By analyzing different bit depths and subsampling schemes, we aim to determine optimized settings that balance compression efficiency with energy consumption, ultimately contributing to more sustainable and high-quality video delivery. We evaluate both encoding and decoding energy consumption and assess the quality of videos using various metrics including PSNR, VMAF, ColorvideoVDP, and CAMBI. Our findings offer valuable insights for video codec developers and content providers aiming to improve the performance and environmental footprint of their video streaming services.

关键词： video encoding video decoding video quality bit depth color subsampling energy

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An Empirical Study of Emotion Recognition from Thermal video Based on Deep Neural Networks

An Empirical Study of Emotion Recognition from Thermal Video...

引用

IEEE International conference on Visual communications and image processing (VCIP)

作者： Prawiro, Herman Pan, Tse-Yu Hu, Min-Chun Natl Tsing Hua Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781728180687

Emotion recognition is a crucial problem in affective computing. Most of previous works utilized facial expression from visible spectrum data to solve emotion recognition task. Thermal videos provide temperature measurement of human body over time, which can be used to recognize affective states by learning its temporal pattern. In this paper, we conduct comparative experiments to study the effectiveness of the existing deep neural networks when applied to emotion recognition task from thermal video. We analyze the effect of various approaches for frame sampling in video, temporal aggregation between frames, and different convolutional neural network architectures. To the best of our knowledge, we are the first work to conduct study on emotion recognition from thermal video based on deep neural networks. Our work can provide preliminary study to design new methods for emotion recognition in thermal domain.

关键词： emotion recognition thermal video deep neural network

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Minimizing transmission energy in wireless video communications

Minimizing transmission energy in wireless video communicati...

引用

International conference on image processing (ICIP 2001)

作者： Eisenberg, Y Pappas, TN Berry, R Katsaggelos, AK Northwestern Univ Dept Elect & Comp Engn Evanston IL 60208 USA

ISBN: (纸本)0780367251

A key constraint in mobile communications is the reliance on a battery with a limited energy supply. Efficiently utilizing the available energy is therefore an important design consideration. In this paper we consider a situation where a video sequence is to be compressed and transmitted over a wireless channel. The goal is to limit the amount of distortion in the received video sequence while using the minimum required transmission energy. To accomplish this goal we consider error resilience and concealment techniques, at the source coding level, as well as the dynamic allocation of physical layer communication resources. We jointly consider these approaches in a novel framework. In this setting we formulate an optimization problem that corresponds to minimizing the energy required to transmit a video frame with an acceptable level of distortion. We present methods for solving this problem and other extensions.

关键词： Wireless telecommunication systems

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Autonomous Visual Moderation System (AutoMod) 31

Autonomous Visual Moderation System (AutoMod)

引用

31st IEEE conference on Signal processing and communications Applications (SIU)

作者： Bahtiyar, Huseyin Katipoglu, Bahadir Irfan Yuksel, Eda Toroslu, Ismail Hakki Karagoz, Pinar VLMedia R&D Dept Gumus Blok K1-1 ODTU TEKNOKENT Ankara Turkiye Middle East Tech Univ METU Dept Comp Engn TR-06800 Ankara Turkiye

ISBN: (纸本)9798350343557

Automod, the content moderation system, is an artificial intelligence solution that enables the detection of similarities and inconsistencies in visual content (image, video, etc.). It is designed as a content moderation system to detect the similarity and inconsistencies of user-generated visual content (images and videos). With the similarity module installed, labor savings of 15% were achieved, and F1 score results of 90% and higher were achieved for nonconformity detection models. More than 100.000 images can be evaluated daily, and the system's load was tested. Similarly, keyframes obtained from at least 65.000 video content that can be evaluated daily were passed through nonconformity models, and load test was applied.

关键词： image processing Machine Learning Deep Learning

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Adaptive Resolution Change for Versatile video Coding

Adaptive Resolution Change for Versatile Video Coding

引用

IEEE International conference on Visual communications and image processing (VCIP)

作者： Chang, Tsui-Shan Sun, Yu-Chen Zhu, Ling Lou, Jian Alibaba Grp Hangzhou Peoples R China Alibaba Grp Bellevue WA USA

ISBN: (纸本)9781728180687

This paper presents an adaptive resolution change (ARC) method adopted in versatile video coding (VVC) to adapt the video bit-stream transmission to dynamic network environments. This approach enables resolution changes within a video sequence at any frame without the insertion of an instantaneous decoder refresh (IDR) or intra random access picture (IRAP). The underlying techniques include reference picture resampling and handling of interactions between the existing coding tools and the changes in resolution. In addition to the techniques adopted in VVC, this paper proposes two techniques for temporal motion vector prediction and deblocking filter to further improve both subjective and objective quality. The experimental results show that the combined ARC method can prevent the burden on bit cost exerted by the insertion of an intra frame during resolution changes. At the same time, 18%, 21% and 21% BD-rate reductions are achieved for Y, Cb, and Cr components, respectively.

关键词： video coding resolution change

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Fast Machine Learning Aided Intra Mode Decision for Real-Time VVC Intra Coding

Fast Machine Learning Aided Intra Mode Decision for Real-Tim...

引用

2024 conference on Visual communications and image processing

作者： Sainio, Joose Ataman, Baran Marie, Alban Mercat, Alexandre Vanne, Jarno Tampere Univ Ultra Video Grp Tampere Finland

ISBN: (纸本)9798331529543;9798331529550

Reducing the huge computational complexity of intra mode decision is the key to real-time video Coding (VVC). This paper proposes a fast intra mode decision scheme that takes advantage of lightweight machine learning (ML) models to classify intra modes into fifteen clusters. The cluster is further refined using one of the three proposed strategies to select the most optimal mode. Our experimental results with the fastest configuration of the practical uvg266 encoder show that the proposed methods yield a competitive rate-distortion-complexity trade-off over a conventional rough mode decision (RMD). To the best of our knowledge, this is the first work to successfully reduce the complexity of RMD in a practical VVC encoder with the use of ML techniques.

关键词： Real-time encoding Versatile video Coding (VVC) intra mode decision machine learning

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No Reference Stereoscopic video Quality Assessment based on Human Vision System

No Reference Stereoscopic Video Quality Assessment based on ...

引用

IEEE International conference on Visual communications and image processing (VCIP)

作者： Zhang, Xiaofang Li, Sumei Tianjin Univ Int Engn Inst Tianjin Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781665475921

In this paper, we propose a no-reference stereoscopic video quality assessment (NR-SVQA) based on human vision system (HVS). Firstly, we build a frequency transform module (FTM), which maps spatial domain to frequency domain by cosine discrete transform (DCT), and selects important frequency components through channel attention mechanism. Secondly, we use dynamic convolution to regionally process the same input. Thirdly, we use convolutional long short term memory (Conv-LSTM) to extract spatio-temporal information rather than just temporal information. Finally, in order to better simulate the visual characteristics of human eyes, we build a optic chiasm module. The experiment results show that our method outperforms any other methods.

关键词： stereoscopic video quality assessment frequency domain human vision system dynamic convolution

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Linear Regression Mode of Intra Prediction for Screen Content Coding

Linear Regression Mode of Intra Prediction for Screen Conten...

引用

IEEE International conference on Visual communications and image processing (VCIP) - Visual communications in the Era of AI and Limited Resources

作者： Peng, Wei Wang, Hongkui Yu, Li Huazhong Univ Sci & Technol Sch Electron Inf & Commun Wuhan Hubei Peoples R China

ISBN: (纸本)9781728185514

High Efficiency video Coding - Screen Content Coding (HEVC-SCC) follows the traditional angular intra prediction technique in HEVC. However, the Planar mode and the DC mode are somewhat repetitive for screen content video with features such as no senor noise. Hence, this paper proposes a new intra prediction mode called linear regression (LR) mode, which combines the Planar mode and the DC mode into one mode. The LR mode improves the prediction accuracy of intra prediction for fading regions in screen content video. Besides, by optimizing the most probable mode (MPM) construction, the hit rate of the best mode in the MPM list is improved. The experimental results show that the proposed method can achieve 0.57% BD-BR reduction compared with HM 16.20+SCM8.8, while the coding time remains largely the same.

关键词： Screen content coding intra prediction high efficiency video coding regression

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Stereoscopic video Quality Assessment with Multi-level Binocular Fusion Network Considering Disparity and Multi-scale Information

Stereoscopic Video Quality Assessment with Multi-level Binoc...

引用

IEEE International conference on Visual communications and image processing (VCIP) - Visual communications in the Era of AI and Limited Resources

作者： Feng, Yingjie Li, Sumei Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781728185514

Stereoscopic video quality assessment (SVQA) is of great importance to promote the development of the stereoscopic video industry. In this paper, we propose a three-branch multi-level binocular fusion convolutional neural network (MBFNet) which is highly consistent with human visual perception. Our network mainly includes three innovative structures. Firstly, we construct a multi-scale cross-dimension attention module (MSCAM) on the left and right branches to capture more critical semantic information. Then, we design a multi-level binocular fusion unit (MBFU) to fuse the features from left and right branches adaptively. Besides, a disparity compensation branch (DCB) containing an enhancement unit (EU) is added to provide disparity feature. The experimental results show that the proposed method is superior to other existing SVQA methods with state-of-the-art performance.

关键词： stereoscopic video quality assessment mufti-scale disparity binocular fusion

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