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About multimedia communication standardization architecture

About multimedia communication standardization architecture

引用

International conference on Signal processing Proceedings (ICSP)

作者： Yumin Feng Wei Xu TianXiang Lu Multimedia Communication Research Section of telecommunication & Control Department Northern Jiaotong University China

ISBN: (纸本)0780329120

From the early days of multimedia communication development, ITU-T has paid much attention to establishing standard systems. In this paper, the authors discuss the ITU-T recommendation H series and T series on audiographic and audio-visual multimedia services along with the research work on multimedia communication which their research lab has been doing and their experience of participating in the research and discussion work on ITU-T standard files on image and multimedia communication which was held by the telecommunication department in order to establish China's own corresponding standards.

关键词： Multimedia communication Standardization Multimedia systems Manufacturing industries communications technology Communication standards Road transportation Information technology ISDN TV broadcasting

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Video action classification by deep learning

Video action classification by deep learning

引用

IEEE Signal processing and communications Applications (SIU)

作者： Esra Ergün Filiz Gürkan Onur Kaplan Bilge Günsel Çoğulortam ışaret İşleme ve Örüntü Tanıma Grubu İstanbul Teknik Üniversitesi İstanbul Türkiye

ISBN: (纸本)9781509064953

The purpose of this study is learning and classification of video activities using video color and motion information. The video activity labeling is important for many applications such as video content modeling, indexing, and quick access to content. In this study video activity recognition is performed by deep learning. In order to learn visual features of video, Convolutional Neural Network (CNN) layers and a special type of recursive networks, Long-Short Term Memory (LSTM), layers are stacked. Video sequence learning is performed by end-to-end training. Recent works on deep learning employ color end motion information together to improve learning and classification accuracy. In this study, unlike the existing models, video motion content is learned using SIFT flow vectors and motion and color features are fused for activity recognition. Performance tests performed on a commonly used benchmarking data set, UCF 101 which includes activity labeled videos from 101 action categories such as "Biking", "Playing Guitar," demonstrate that SIFT flow vectors allow us to model motion information more accurately than optical flow vectors and increase video motion classification performance.

关键词： Machine learning Art Neural networks image color analysis Activity recognition image motion analysis Computer vision

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An unconstrained method for lip detection in color images

An unconstrained method for lip detection in color images

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Evangelos Skodras Nikolaos Fakotakis Artificial Intelligence Group Wire Communications Laboratory Department of Electrical and Computer Engineering University of Patras Patras Greece

The use of visual information derived from accurate lip extraction, can provide features invariant to noise perturbation for speech recognition systems and can be also used in a wide variety of applications. Unlike many current automatic lip reading systems which impose several restrictions on users, our efforts are towards an unconstrained system. In this paper we introduce a method using k-means color clustering with automatically adapted number of clusters, for the extraction of the lip area. The method's performance is improved by previously applying nearest neighbor color segmentation. The extracted lip area is morphologically processed and fitted by a best-fit ellipse. The points of interest (keypoints) of the mouth area are extracted, while a corner detector for fine tuning of mouth corners is applied. Experimental tests have shown that the algorithm works very well under natural conditions and accurate extraction of lip keypoints is feasible.

关键词： image color analysis image segmentation Lips Databases Feature extraction Mouth Lighting

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Multi-Direction Strategy with Honey Badger Algorithm and Convolutional Neural Network for Industrial Robot visual Servo image processing

Multi-Direction Strategy with Honey Badger Algorithm and Con...

引用

Intelligent Algorithms for Computational Intelligence Systems (IACIS), International conference on

作者： Hao Chen Deppartment of Engineering & Mechanics Jilin Communications Polytechnic Changchun China

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

The Industrial robot visual servo image processing requires highly autonomous and intelligence robotic manipulators, with goal of performing manipulation tasks independently without human interventions. However, limit efficiency for large scale, sensitive to noise in input data which affect classification accuracy. This paper, proposed Multi-Direction Strategy with Honey Badger Algorithm (MHBA) and Convolutional Neural Network (CNN) for classification is effectively explore the hyper parameter space of CNN technique is help achieve classification accuracy. The MHBA ability to adapt and explore multiple directions in the parameter space makes CNN maximum efficient to variation in input data. The MHBA model is applied to large scale CNN model is efficiently narrowing down the search space and balances exploration and exploitation allowing for search space. The Pre-processing using linear transformation such as translation or rotation help in adjusting the image dimension while maintaining the essential content. The proposed MHBA-CNN technique for industrial robot is achieving better outcomes such as Mean Absolute Error (MAE) of 2.03, Mean Absolute Scaled Error (MASE) of 3.45, R 2 score of 2.45 on raw dataset. The existing technique such as Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) are evaluated of proposed method.

关键词： Adaptation models visualization Recurrent neural networks Accuracy Industrial robots Space exploration Classification algorithms Convolutional neural networks Servomotors Long short term memory

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Facial feature extraction and image-based face drawing

Facial feature extraction and image-based face drawing

引用

International conference on Signal processing Proceedings (ICSP)

作者： Hao Wang Kongqiao Wang Visual Communications Laboratoly Nokia Research Center Beijing China

ISBN: (纸本)0780374886

This paper describes algorithms to extract features of facial organs such as eyes, eyebrows, mouth, nose and borders of other parts. Based on these extracted organs, automatic face drawing is generated, which embodies the individual features that the face looks more likely to be so. At first face detection is implemented by using horizontal textures and eigenfaces. After that, the pair of irises are located using the Hough-transform and intensity valley correlation. Then other organs are extracted based on the skeleton characteristic of the face. For face drawing generating, contours are rendered with multi-values, facial skin color is smoothed, and features are strengthened in order to get impressive effects.

关键词： Facial features Face detection Feature extraction Eyes Eyebrows Mouth Nose Waveguide discontinuities Skeleton Skin

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CSC-Net: A Lightweight Model for Remote Real-Time Monitoring of Infrared Small Targets

CSC-Net: A Lightweight Model for Remote Real-Time Monitoring...

引用

Future communications and Networks (FCN), International conference on

作者： Mingjin Zhang Nan Zhou Xiaofeng Li Xiaogang Dong Luchang Yang Yunsong Li Xidian University Xi’an China Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9798350396034

ISBN: (纸本)9798350396041

Infrared small target detection (IRSTD) is an important subject in many fields such as real-time monitoring and drone applications. Drones typically require real-time processing and transmission of infrared image data during flight. Lightweight models can reduce computational and communication burdens. While existing methods perform target detection effectively, resource-intensive demands hinder remote real-time detection. To provide high-performance target detection and analysis in resource-constrained environments, we propose a cross-sensing compression network (CSC-Net) for IRSTD in this paper. Specifically, the compression mixer module (CMM) enhances the hybrid scheme’s adaptability to different locations by exploring both semantic and spatial dimensions, thus improving image association flexibility. The filter perception module (FPM) dynamically adjusts input contributions for enhanced cross-sensing, emphasizing the benefits of multilayered semantics. Experiments on SIRST and IRSTD-1K show that the proposed CSC-Net can achieve accurate target location and segmentation. In particular, its visual effects and resource consumption can meet the remote real-time monitoring scenario.

关键词： Adaptation models image segmentation image coding Computational modeling Semantics Object detection visual effects

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Technology against vision architectures

Technology against vision architectures

引用

International conference on Massively Parallel Computing Systems

作者： B. Zavidovique IEF University of Paris XI Orsay France

Understanding what the problems are in robot-vision architecture, requires a better comparison of major features. But a zoology of vision machines is questioned when, aiming for a well informed architectural feature choice, a rapid presentation of technological trends in the field is proposed. Then an approach closer to physics prompts to a classification from a control point of view: it reveals some duality between operations and communications. A few visual operations are distinguished provided technology is not trailing behind. But emphasis should be put on communication networks, although they do not show any image processing specificity currently, and the conclusion addresses some limits in that respect.< >

关键词： image processing Zoology Communication system control Stress Communication networks Very large scale integration Application specific integrated circuits Morphology Assembly systems Robot vision systems

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Turkish image Captioning with Vision Transformer Based Encoders and Text Decoders

Turkish Image Captioning with Vision Transformer Based Encod...

引用

IEEE Signal processing and communications Applications (SIU)

作者： Serdar Yıldız Abbas Memiş Songül Varlı Bilgisayar Mühendisliği Bölümü Yıldız Teknik Üniversitesi İstanbul Türkiye BİLGEM TÜBİTAK Kocaeli Türkiye Bilgisayar Mühendisliği Bölümü İstanbul Üniversitesi İstanbul Türkiye Türkiye Sağlık Enstitüleri Başkanlığı İstanbul Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

image captioning is defined as the process of describing of images by computer systems automatically. Thus, visual information regarding the content of the images is expressed in textual form. This paper presents a deep learning-based Turkish image captioning study implemented by using vision transformers and text decoders. In the proposed study, images are initially encoded with a vision transformer-based module. Afterwards, the features of the encoded image are normalized by passing them through a feature projection module. In the final stage, image captions are generated via a text decoder block. To test the performance of the Turkish image captioning system presented in this paper, TasvirEt, a benchmark dataset consisting of Turkish image captions, was used. In the tests performed, quite successful results were observed and a BLEU-1 value of 0.3406, a BLEU-2 value of 0.2110, a BLEU-3 value of 0.1253, a BLEU-4 value of 0.0690, a METEOR value of 0.1610, a ROUGE-L value of 0.3145 and a CIDEr value of 0.3879 were measured.

关键词： Computer vision visualization Signal processing Benchmark testing Transformers Decoding Meteors

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A fuzzy logic approach for the fast approximate computation of image transforms from block JPEG DCT coefficients

A fuzzy logic approach for the fast approximate computation ...

引用

IEEE International conference on Automation, Quality and Testing, Robotics, AQTR

作者： Mihaela Gordan Serban Meza Mihaela Cislariu Bogdan Orza Aurel Vlaicu Dorina Capatina Ioan Stoian Department of Communications Technical University of Cluj-Napoca Cluj-Napoca Romania S.C. IPA S.A. Subsidiary CIFATT Cluj Cluj-Napoca Romania

Computationally efficient implementation of different image processing and analysis algorithms is crucial in many modern real world applications. Several modern visual analytics applications involve processing large amounts of compressed image/video data on restricted hardware resources, in a numerically efficient manner. In this context, the formulation of some image analysis/processing algorithms in the compressed image/video domain can bring significant benefits in the computational complexity reduction. An important step to image analysis, feature extraction, based on unitary image transforms is addressed in this paper, in a general form. Starting from the fact that in most popular video compression the intraframes are block discrete cosine transform (DCT) encoded, we present and propose a solution to computing any unitary image transform at pixels block level, starting from the DCT coefficients of the block. Since approximate forms of the transforms are often satisfactory, we propose a fuzzy logic system based approach to optimize the computational complexity with minimal loss of image information. The method is exemplified for the case of the Walsh transform, which shows that even the fastest implementation provides (by reconstruction) images of good quality.

关键词： Discrete cosine transforms Transform coding image coding Quantization (signal) Fuzzy logic Algorithm design and analysis

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Laplacian based structure-aware error diffusion

Laplacian based structure-aware error diffusion

引用

IEEE International conference on image processing

作者： Han-Sang Lee Kang-Kook Kong Ki-Sang Hong Department of Computer and Communications Engineering Postech Pohang South Korea Department of Electronic and Electrical Engineering Postech Pohang South Korea

In this paper, we propose a new halftoning scheme that preserves the structure and tone similarities of images while maintaining the simplicity of Floyd-Steinberg error diffusion. Our algorithm is based on the Floyd-Steinberg error diffusion algorithm, but the threshold modulation part is modified to improve the over-blurring issue of the Floyd-Steinberg error diffusion algorithm. By adding some structural information on images obtained using the Laplacian operator to the quantizer thresholds, the structural details in the textured region can be preserved. The visual artifacts of the original error diffusion that is usually visible in the uniform region is greatly reduced by adding noise to the thresholds. This is especially true for the low contrast region because most existing error diffusion algorithms cannot preserve structural details but our algorithm preserves them clearly using threshold modulation. Our algorithm has been evaluated using various types of images including some with the low contrast region and assessed numerically using the MSSIM measure with other existing state-of-art halftoning algorithms. The results show that our method performs better than existing approaches both in the textured region and in the uniform region with the faster computation speed.

关键词： visualization Algorithm design and analysis image edge detection Laplace equations Modulation Pixel Noise

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