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检索条件"任意字段=2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023"

共 2299 条记录，以下是291-300 订阅

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MAESR360: Masked autoencoder-based 360-degree video streaming via multi-scale feature fusion

MAESR360: Masked autoencoder-based 360-degree video streamin...

引用

2024 conference on visual communications and image processing

作者： Yu, Li Pang, Zhiyu Gabbouj, Moncef Nanjing Univ Informat Sci & Technol Sch Comp Sci Nanjing Peoples R China Tampere Univ Dept Comp Sci Tampere 33100 Finland

ISBN: (纸本)9798331529543;9798331529550

360-degree video streaming is becoming increasingly popular for its immersive experience. Traditional adaptive tile-based streaming methods allocate the bitrates according to viewport prediction, which effectively reduces required transmission bandwidth, but it will cause serious quality degradation when the viewport prediction is inaccurate. Thus, some researchers propose visual reconstruction and enhancement-based 360-degree video streaming framework, which can reconstructs the whole frame at very low bitrates. However, existing frameworks are built upon image-based visual reconstruction methods, which do not fully consider the characteristics of videos. In this paper, we propose a masked autoencoder-based, multi-scale optimized framework for 360-degree video streaming (MAESR360), which fully considers the temporal relevance of the video. We utilize spatio-temporal downsampling and high-ratio tube masking strategies to effectively reduce the amount of transmitted data. Additionally, we design a lightweight visual reconstruction model based on multi-scale feature fusion to recover the visual quality of video frames. The effectiveness of our proposed method is demonstrated through extensive experiments.

关键词： 360-degree video tube masking visual reconstruction multi-scale feature fusion

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Adaptive Block-Level Quality Parameter Adjustment Towards Low Video Bit-Rate Fluctuation

Adaptive Block-Level Quality Parameter Adjustment Towards Lo...

引用

2024 conference on visual communications and image processing

作者： Feng, Longtao Yin, Qian Ren, Huiwen Wang, Zhao Ma, Siwei He, Yuwen Peking Univ Natl Engn Res Ctr Visual Technol Sch Comp Sci Beijing Peoples R China Peking Univ Adv Inst Informat Technol Beijing Peoples R China Bytedance Inc San Diego CA USA

ISBN: (纸本)9798331529543;9798331529550

Existing quantization parameter (QP) adjustment methods in video coding often focus solely on coding efficiency and ignore the impact of bit-rate fluctuations on video transmission and bandwidth waste. This is mainly because intra pictures, in a hierarchical coding structure, are allocated smaller QP and thus consume more bits. To address this issue, we propose an adaptive block-level QP adjustment method. Specifically, intra picture importance (IPI) is first introduced to evaluate the adjustability of intra picture QP. For intra pictures whose QP can be adjusted, we further propose block importance (BI) to determine their optimal block-level QP adjustment. Experimental results show that our proposed method reduce the bit-rate fluctuations while basically maintaining the coding performance. Notably, significant improvements can be observed in high-resolution videos, with a reduction of approximately 11% in bit-rate fluctuations.

关键词： Video Coding Quantization Parameter Bit-Rate Fluctuation

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MRIQA: Subjective Method and Objective Model for Magnetic Resonance image Quality Assessment

MRIQA: Subjective Method and Objective Model for Magnetic Re...

引用

ieee international conference on visual communications and image processing (vcip)

作者： Chen, Qi Liu, Fang Duan, Huiyu Wang, Yao Min, Xiongkuo Zhou, Yan Zhai, Guangtao Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Med Renji Hosp Dept Radiol Shanghai Peoples R China

ISBN: (纸本)9781665475921

Magnetic Resonance Imaging (MRI) is widely used for medical diagnosis, staging and follow-up of disease. However, MRI images may have artifacts due to various reasons such as patient movement or machine distortion, which may be unintentionally introduced during the procedure of medical image acquisition, processing, etc. These artifacts may affect the effectiveness of diagnosis or even cause false diagnosis. To solve this problem, we propose a general medical image quality assessment (MIQA) methodology, including subjective MIQA procedures and objective MIQA algorithms. We further apply this methodology to MRI images in this paper due to its widespread use in practical applications. We first establish a magnetic resonance imaging quality assessment (MRIQA) database, which contains 3809 MRI images. Then a subjective image quality assessment experiment is conducted by expert doctors according to the diagnostic value of these images, which split all MRI images into 1285 low quality images and 2524 high quality images. We then conduct a baseline deep learning experiment, and propose an attention based MIQANet model to automatically separate MRI images into high quality and low quality based on their diagnosis value. Our proposed method achieves a great quality assessment accuracy of 96.59%. The constructed MRIQA database and proposed MIQA model will be public available to further promote medical IQA research.

关键词： Medical image Quality Assessment Database Deep Learning

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Efficient Bitrate Ladder Construction for Per-Shot Adaptive Encoding

Efficient Bitrate Ladder Construction for Per-Shot Adaptive ...

引用

2024 conference on visual communications and image processing

作者： Zhao, Yan Cheng, ZhengXue Lu, Guo Xie, Rong Song, Li Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9798331529543;9798331529550

HTTP adaptive streaming (HAS) constructs bitrate ladders to deliver videos with the best possible quality under varying network conditions. Though per-shot content adaptive encoding (CAE) largely improves the compression efficiency by constructing the optimal bitrate ladder for each video shot, it suffers from excessive encoding complexity as all the points in the operating space (typically resolution x bitrate) need to be encoded and compared. To address this issue, this paper proposes an efficient bitrate ladder construction method that encodes only a subset of operating points, then uses curve fitting and inter-curve prediction to estimate other points' RD performance. The proposed method enables low-complexity ladder construction even for high-dimension operating spaces that incorporate dimensions like encoding presets. Experiments show that this method can achieve RD performance comparable to the original per-shot CAE with only 42% encoding points. Even when minimizing the encoding points to 3.6% of the original CAE, it achieves 15% BDRate improvements compared to using the fixed bitrate ladder.

关键词： Content-adaptive encoding per-shot encoding bitrate ladder prediction adaptive streaming

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End-to-end Prediction of Streaming Video Quality of Experience: Dataset and Approach

End-to-end Prediction of Streaming Video Quality of Experien...

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2024 conference on visual communications and image processing

作者： Jia, Ziheng Min, Xiongkuo Zhai, Guangtao Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9798331529543;9798331529550

With the rapid development of video-on-demand (VOD) and real-time streaming video technologies, the accurate objective assessment of streaming video Quality of Experience (QoE) has become a focal point for optimizing streaming-related technologies. However, due to the inherent transmission distortions caused by poor Quality of Service (QoS) conditions in streaming videos, such as intermittent stalling, rebuffering, and drastic changes in video sharpness due to bitrate fluctuations, evaluating streaming video QoE presents numerous challenges. This paper introduces a large and diverse in-the-wild streaming video QoE evaluation dataset - the SJLIVE-1k dataset. This work addresses the limitations of corresponding datasets, which lack in-the-wild video sequences under real network conditions and whose amount of video content is insufficient. Furthermore, we propose an end-to-end objective QoE evaluation strategy that extracts video content and QoS features from the video itself without using any extra information. By implementing self-supervised contrastive learning as the "reminder" to bridge the gap between the different types of features, our approach achieves state-of-the-art results across three datasets. Our proposed dataset will be released to facilitate further research.

关键词： Quality of Experience streaming videos contrastive learning

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ADAPTIVE HIGH-FREQUENCY CLIPPING FOR IMPROVED image QUALITY ASSESSMENT

ADAPTIVE HIGH-FREQUENCY CLIPPING FOR IMPROVED IMAGE QUALITY ...

引用

ieee international conference on visual communications and image processing (vcip)

作者： Gu, Ke Zhai, Guangtao Liu, Min Xu, Qi Yang, Xiaokang Zhou, Jun Zhang, Wenjun Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Shanghai 200030 Peoples R China Shanghai Key Lab Digital Media Proc & Transmiss Shanghai 200030 Peoples R China

ISBN: (纸本)9781479902880

It is widely known that the human visual system (HVS) applies multi-resolution analysis to the scenes we see. In fact, many of the best image quality metrics, e.g. MS-SSIM and IW-PSNR/SSIM are based on multi-scale models. However, in existing multi-scale type of image quality assessment (IQA) methods, the resolution levels are fixed. In this paper, we examine the problem of selecting optimal levels in the multi-resolution analysis to preprocess the image for perceptual quality assessment. According to the contrast sensitivity function (CSF) of the HVS, the sampling of visual information by the human eyes approximates a low-pass process. For images, the amount of information we can extract depends on the size of the image (or the object(s) inside) as well as the viewing distance. Therefore, we proposed a wavelet transform based adaptive high-frequency clipping (AHC) model to approximate the effective visual information that enters the HVS. After the high-frequency clipping, rather than processing separately on each level, we transform the filtered images back to their original resolutions for quality assessment. Extensive experimental results show that on various databases (LIVE, IVC, and Toyama-MICT), performance of existing image quality algorithms (PSNR and SSIM) can be substantially improved by applying the metrics to those AHC model processed images.

关键词： image quality assessment (IQA) image size viewing distance scale transform high-frequency clipping

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AN ANALYTICAL STUDY OF SUBPIXEL-BASED image DOWN-SAMPLING PATTERNS IN FREQUENCY DOMAIN

AN ANALYTICAL STUDY OF SUBPIXEL-BASED IMAGE DOWN-SAMPLING PA...

引用

ieee international conference on visual communications and image processing (vcip)

作者： Ling, Yonggen Au, Oscar C. Tang, Ketan Pang, Jiahao Zeng, Jin Fang, Lu Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781479902880

Subpixel-based image down-sampling is a class of methods that can provide improved apparent resolution of the down-scaled image compared to the pixel-based methods. The frequency characteristics of all possible subpixel-based down-sampling patterns for RGB vertical stripes are analytically studied in this paper. Our proposed algorithm reveals that there are merely seven equivalent energy distributions in the luminance frequency spectrum. To achieve higher luminance resolution, we then calculate and choose the optimal down-sampling pattern with anti-aliasing low-pass filter designed for it so as to maximize the energy of the luminance component within the cut-off shape. Experimental results show that the proposed method provides sharper images compared to the state-of-art subpixel-based methods, with little color distortion.

关键词： subpixel image down-sampling frequency analysis

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MEDO: Minimizing Effective Distortions only for Machine-Oriented visual Feature Compression

MEDO: Minimizing Effective Distortions only for Machine-Orie...

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2023 ieee international conference on visual communications and image processing, vcip 2023

作者： Yoon, Curie Lim, Dalhong Kim, Yeongwoong Jeong, Hyewon Kim, Hui Yong Lee, Jooyoung Kim, Younhee Jeong, Se Yoon Kyung Hee University School of Computing Gyeonggi Korea Republic of Research Institute Electronics and Telecommunications Daejeon Korea Republic of

ISBN: (纸本)9798350359855

In search for efficient feature compression technologies for machine consumption, MPEG recently issued a call for proposal (CfP) on feature compression for video coding for machine (FCVCM). One issue in feature compression is that the input feature maps generally have high redundancy in them. Various researches to reduce such redundancy have been made. For example, a recent study called L-MSFC (learnable multi-scale feature compression), which effectively combines multi-scale feature fusion and compression in an end-To-end learnable framework, showed up to 98% BD rate gain over the anchor model defined in the FCVCM CfP. Despite these advances in FCVCM, relation between distortions in feature maps and performance of vision tasks has stayed relatively unexplored. In this paper, we propose a novel loss function called MEDO (minimizing effective distortions only) based on our hypothesis that distortions below some threshold do not improve task performance. Experimental results on instance segmentation task show that our MEDO loss on top of L-MSFC improves the overall rate-mAP performance without compromising complexity. Being more practical for real-world uses, we also present an extension to L-MSFC for variable-rate support with a single model. © 2023 ieee.

关键词： Redundancy

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visual Analysis of Human Motion: A Survey on Recent Advances and Applications 33

Visual Analysis of Human Motion: A Survey on Recent Advances...

引用

33rd ieee international conference on visual communications and image processing, vcip 2018

作者： Wang, Qifei Rao, Yunbo Dept. EECS University of California Berkeley BerkeleyCA94720 United States Chengdu Sichuan China

ISBN: (纸本)9781538644584

This paper summarizes the recent progress in human motion analysis and its applications. The first part of this paper reviews the motion capture systems and the representations of human's motion data. Next, the paper sketches the advanced human motion data processing technologies, including motion data filtering, temporal alignment, and segmentation. The following parts overview the state-of-the-art approaches of action recognition and dynamics measuring. The last part discusses the emerging applications of human motion analysis in healthcare and human robot interaction. The promising research topics of human motion analysis in the future are also summarized in the last part. © 2018 ieee.

关键词： Human robot interaction

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A Fully Automatic Approach for Fisheye Camera Calibration 33

A Fully Automatic Approach for Fisheye Camera Calibration

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33rd ieee international conference on visual communications and image processing (ieee vcip)

作者： Tai, Yen-Chou Hsieh, Yi-Yu Chuang, Jen-Hui Natl Chiao Tung Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781538644584

An automatic calibration procedure for a fisheye camera is presented in this paper by employing a flat panel monitor. The procedure does not require precise camera-monitor alignment, and any manual input of data or commands, making it useful for factory automation for mass production of such cameras. The fully automatic calibration procedure, which requires the generation of various test patterns on the display, and analysis of fisheye images of these patterns, consists of the following steps: (i) estimate the image center of the camera, (ii) identify the line on the monitor which intersects optical axis of the camera perpendicularly, and (iii) along the above line, obtain calibration data needed in de-warping the fisheye image. Experimental results demonstrate that the proposed approach performs satisfactorily in terms of effectiveness and accuracy.

关键词： fisheye camera automatic calibration image center ellipse fitting image de-warping

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