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检索条件"任意字段=Conference on Visual Communications and Image Processing 96"

共 3879 条记录，以下是91-100 订阅

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visual Analysis Motivated Super-Resolution Model for image Reconstruction

Visual Analysis Motivated Super-Resolution Model for Image R...

引用

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

作者： Wang, Huifen Xue, Junda Yang, Mingchuan Zhang, Yuan China Telecom Res Inst Coll Big Data & Artificial Intelligence Shanghai Peoples R China China Telecom Res Inst Coll Big Data & Artificial Intelligence Beijing Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China China Telecom Res Inst Coll Big Data & Artificial Intelligence Hangzhou Peoples R China

ISBN: (纸本)9781665475921

This paper presents a concise end-to-end visual analysis motivated super-resolution model VASR for image reconstruction. Compatible with the existing machine vision feature coding framework, the features extracted from the machine vision task model are super-resolution amplified to reconstruct the original image for human vision. The experimental results show that without additional bit-streams, VASR can well complete the task of image reconstruction based on the extracted machine features, and has achieved good results on COCO, Openimages, TVD, and DIV2K datasets.

关键词： coding for machines image reconstruction super-resolution

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Graph Grouping Loss for Metric Learning of Face image Representations

Graph Grouping Loss for Metric Learning of Face Image Repres...

引用

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

作者： Inoue, Nakamasa Tokyo Inst Technol Tokyo Japan

ISBN: (纸本)9781728180687

This paper proposes Graph Grouping (GG) loss for metric learning and its application to face verification. GG loss predisposes image embeddings of the same identity to be close to each other, and those of different identities to be far from each other by constructing and optimizing graphs representing the relation between images. Further, to reduce the computational cost, we propose an efficient way to compute GG loss for cases where embeddings are L-2 normalized. In experiments, we demonstrate the effectiveness o(f) the proposed method for face verification on the VoxCeleb dataset. The results show that the proposed GG loss outperforms conventional losses for metric learning.

关键词： Face recognition

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Alpha-trimmed Mean Filter and XOR based image Enhancement for Embedding Data in image

Alpha-trimmed Mean Filter and XOR based Image Enhancement fo...

引用

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

作者： Alam, S. M. Ammar Ul Huda, Moid Farhan, Muhammad Habib Univ Dhanani Sch Sci & Engr Karachi Pakistan

ISBN: (纸本)9781728185514

In the age of digital content creation and distribution, steganography, that is, hiding of secret data within another data is needed in many applications, such as in secret communication between two parties, piracy protection, etc. In image steganography, secret data is generally embedded within the image through an additional step after a mandatory image enhancement process. In this paper, we propose the idea of embedding data during the image enhancement process. This saves the additional work required to separately encode the data inside the cover image. We used the Alpha-Trimmed mean filter for image enhancement and XOR of the 6 MSBs for embedding the two bits of the bitstream in the 2 LSBs whereas the extraction is a reverse process. Our obtained quantitative and qualitative results are better than a methodology presented in a very recent paper.

关键词： steganography alpha-trimmed mean LSB manipulation image enhancement data embedding

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A Vision Based Fish processing System

A Vision Based Fish Processing System

引用

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

作者： Zhang, Zongjian Yu, Litao Zhang, Jian Wu, Qiang Univ Technol Sydney Sydney NSW Australia

ISBN: (纸本)9781728180687

The digital fish provenance and quality tracking system is essential for the seafood supply chain. As a part of this system, we develop a vision-based fish processing system to automatically perform fish freshness estimation, size measurement and species classification. Under the constrained illumination environment, our system is able to auto-process the fish selection, thus greatly reduce the human labour and bring trust and efficiency to the seafood supply chain from catch to market.

关键词： Fish

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Residential Real Estate image Classification for Property Valuation

Residential Real Estate Image Classification for Property Va...

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28th International conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2024, and 23rd International conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

作者： Nejad, Mehrdad Ziaee Naderpour, Mohsen Behbood, Vahid Ramezani, Fahimeh Lu, Jie 15 Broadway UltimoNSW2007 Australia

ISBN: (纸本)9783031859328

Residential real estate price is one of the key components of our economic developments and has also been a major concern of the public, bank industry, government, and investors. The accurate estimation of the sale price and its changes have an important role in the decision-making of related departments and organizations. In Australia, one of the biggest investments for people is in residential real estate. Therefore, many studies and research works have been carried out to build an automated valuation model to predict sale prices of residential properties accurately as much as possible. Automatic and accurate image classification of residential real estate plays an important role in property valuation and decision making of both sellers and buyers. It can be used in real estate online websites to organize the images for each property or used as a component in a visual decision support system for predicting the property sale prices based on property images. As convolutional image classification models show valuable performance in comparison with traditional models, a convolutional classification model is developed in this paper which creates a highly reliable classification component to be used in the corresponding research areas. The performance of the proposed model is investigated through a real dataset of New Sales Wales, Australia. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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RDPlot - An Evaluation Tool for Video Coding Simulations

RDPlot - An Evaluation Tool for Video Coding Simulations

引用

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

作者： Schneider, Jens Sauer, Johannes Wien, Mathias Rhein Westfal TH Aachen Inst Nachrichtentech Aachen Germany Rhein Westfal TH Aachen Lehrstuhl Bildverarbeitung Aachen Germany

ISBN: (纸本)9781728185514

RDPlot is an open source GUI application for plotting Rate-Distortion (RD)-curves and calculating Bjontegaard Delta (BD) statistics [1]. It supports parsing the output of commonly used reference software packages, parsing ∗.csv-formatted files, and ∗.xml-formatted files. Once parsed, RDPlot offers the ability to evaluate video coding results interactively. Conceptually, several measures can be plotted over the bitrate and BD measurements can be conducted accordingly. Moreover, plots and corresponding BD statistics can be exported, and directly integrated into LaTeX documents. © 2021 IEEE.

关键词： image coding

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Estimation of accelerated motion for motion-compensated frame interpolation

Estimation of accelerated motion for motion-compensated fram...

引用

conference on visual communications and image processing 96

作者： Csillag, P Boroczky, L KFKI RES INST MEASUREMENT & COMP TECHH-1525 BUDAPESTHUNGARY

ISBN: (纸本)0819421030

In motion-compensated processing of image sequences, e.g. in frame interpolation, frame rate conversion, deinterlacing, motion blur correction, image sequence restoration, slow-motion replay, etc., the knowledge of motion is essential. In these applications motion information has to be determined from the image sequence. Most motion estimation algorithms use only a simple motion model, and assume linear constant speed motion. The contribution of our paper is the development of an algorithm for modeling and estimation of accelerated motion trajectories, based on a second order motion model. This model is more general and much closer to the real motion present in natural image sequences. The parameters of the accelerated motion are determined from two consecutive motion fields, that has been estimated from three consecutive image frames using a multiresolution pel-recursive Wiener-based motion estimation algorithm. The proposed algorithm was successfully tested on artificial image sequences with synthetic motion as well as on natural real-file videophone and videoconferencing sequences in a frame interpolation environment.

关键词： motion estimation motion compensation acceleration accelerated motion optical flow frame interpolation motion trajectory pel-recursive motion estimation video coding video processing

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Binocular visual Mechanism Guided No-Reference Stereoscopic image Quality Assessment Considering Spatial Saliency

Binocular Visual Mechanism Guided No-Reference Stereoscopic ...

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, Jinhui Li, Sumei Chang, Yongli Tianjin Univ Tianjin Int Engn Inst Tianjin Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781728185514

In recent years, with the popularization of 3D technology, stereoscopic image quality assessment (SIQA) has attracted extensive attention. In this paper, we propose a two-stage binocular fusion network for SIQA, which takes binocular fusion, binocular rivalry and binocular suppression into account to imitate the complex binocular visual mechanism in the human brain. Besides, to extract spatial saliency features of the left view, the right view, and the fusion view, saliency generating layers (SGLs) are applied in the network. The SGL apply multi-scale dilated convolution to emphasize essential spatial information of the input features. Experimental results on four public stereoscopic image databases demonstrate that the proposed method outperforms the state-of-the-art SIQA methods on both symmetrical and asymmetrical distortion stereoscopic images.

关键词： stereoscopic image quality assessment binocular visual mechanism spatial saliency convolutional neural network

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Parallelized Context Modeling for Faster image Coding

Parallelized Context Modeling for Faster Image Coding

引用

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

作者： Koyuncu, A. Burakhan Cui, Kai Boev, Atanas Steinbach, Eckehard Tech Univ Munich Chair Media Technol Munich Germany Huawei Munich Res Ctr Audiovideo Technol Lab Munich Germany

ISBN: (纸本)9781728185514

Learning-based image compression has reached the performance of classical methods such as BPG. One common approach is to use an autoencoder network to map the pixel information to a latent space and then approximate the symbol probabilities in that space with a context model. During inference, the learned context model provides symbol probabilities, which are used by the entropy encoder to obtain the bitstream. Currently, the most effective context models use autoregression, but autoregression results in a very high decoding complexity due to the serialized data processing. In this work, we propose a method to parallelize the autoregressive process used for image compression. In our experiments, we achieve a decoding speed that is over 8 times faster than the standard autoregressive context model almost without compression performance reduction.

关键词： image compression

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No-Reference Stereoscopic image Quality Assessment Based on The visual Pathway of Human visual System

No-Reference Stereoscopic Image Quality Assessment Based on ...

引用

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

作者： Meng, Fan Li, Sumei Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781728185514

With the development of stereoscopic imaging technology, stereoscopic image quality assessment (SIQA) has gradually been more and more important, and how to design a method in line with human visual perception is full of challenges due to the complex relationship between binocular views. In this article, firstly, convolutional neural network (CNN) based on the visual pathway of human visual system (HVS) is built, which simulates different parts of visual pathway such as the optic chiasm, lateral geniculate nucleus (LGN), and visual cortex. Secondly, the two pathways of our method simulate the 'what' and 'where' visual pathway respectively, which are endowed with different feature extraction capabilities. Finally, we find a different application way for 3D-convolution, employing it fuse the information from left and right view, rather than just extracting temporal features in video. The experimental results show that our proposed method is more in line with subjective score and has good generalization.

关键词： Stereoscopic image quality assessment (SIQA) Convolutional neural network (CNN) the human visual system (HVS) 3D-convolution (C3D)

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