Conferences related to IEEE Multimedia

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ICC 2021 - IEEE International Conference on Communications

IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.


2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)

IEEE CCNC 2020 will present the latest developments and technical solutions in the areas of home networking, consumer networking, enabling technologies (such as middleware) and novel applications and services. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions.


2020 IEEE International Conference on Consumer Electronics (ICCE)

The International Conference on Consumer Electronics (ICCE) is soliciting technical papersfor oral and poster presentation at ICCE 2018. ICCE has a strong conference history coupledwith a tradition of attracting leading authors and delegates from around the world.Papers reporting new developments in all areas of consumer electronics are invited. Topics around the major theme will be the content ofspecial sessions and tutorials.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


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Periodicals related to IEEE Multimedia

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


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Most published Xplore authors for IEEE Multimedia

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Xplore Articles related to IEEE Multimedia

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Hand gesture recognition from kinect depth images

2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015

In this study, hand gesture classification method based on depth images is proposed. The proposed method is composed of thresholding, feature extraction, feature selection and classification stages. Hand segmentation on the depth images is carried out based on interval thresholding, curvature scale space is used for feature extraction, sequential feature selection is considered for feature selection and K-Nearest Neighbor method ...


Real-time HEVC decoding with OpenHEVC and OpenMP

2017 IEEE International Conference on Consumer Electronics (ICCE), 2017

HEVC codecs will replace H.264 ones inside the consumer electronic devices in the near future. In this work, the open source OpenHEVC decoder has been modified in order to support parallel decoding at the slice level using OpenMP instead of pthreads. The advantage of this unthreaded decoder is that it can be used with any architecture, providing it supports OpenMP. ...


Real-Time Lightweight CNN for Detecting Road Object of Various Size

2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 2018

This paper proposed a novel lightweight convolutional neural network suitable for road object detection which not only for small objects, but for large objects. The proposed network outperformed detection performance of existing convolutional neural networks on KITTI datasets and satisfied real-time processing speed of 10ms on PC and 65ms on NVIDIA TX2. The model is suitable for running in an ...


Adaptive reference frame selection for near-duplicate video shot detection

2010 IEEE International Conference on Image Processing, 2010

Near-duplicate video shots provide critical visual link between videos and detecting such video shots efficiently and effectively is of paramount importance in many applications such as detecting copyright infringement. In this paper, we propose an improved near-duplicate video shot detection approach by adaptively selecting reference frames for more effective shot representation. The correlation between adjacent frames is measured with Pearson's ...


Efficient distortion model based on H.264

2011 International Conference on Computer Science and Service System (CSSS), 2011

Bused on the study of classic distortion model, Discussed the impact of correlation of video image on the distortion model. According to the distribution of DCT coefficient, a efficient distortion model is proposed which overcomes the shortcoming of the classic distortion model without considering the correlation among pixels.


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Educational Resources on IEEE Multimedia

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IEEE-USA E-Books

  • Hand gesture recognition from kinect depth images

    In this study, hand gesture classification method based on depth images is proposed. The proposed method is composed of thresholding, feature extraction, feature selection and classification stages. Hand segmentation on the depth images is carried out based on interval thresholding, curvature scale space is used for feature extraction, sequential feature selection is considered for feature selection and K-Nearest Neighbor method is used for classification. The performance evaluation of the proposed method is tested on 1000 sampled dataset. Experimental works show that the hand gestures which indicate from 0 to 9 can be recognized with 98.33 % accuracy. This accuracy rate is about 4% better than the compared method.

  • Real-time HEVC decoding with OpenHEVC and OpenMP

    HEVC codecs will replace H.264 ones inside the consumer electronic devices in the near future. In this work, the open source OpenHEVC decoder has been modified in order to support parallel decoding at the slice level using OpenMP instead of pthreads. The advantage of this unthreaded decoder is that it can be used with any architecture, providing it supports OpenMP. Tests have been carried out with three different multicore chips and the performance results are similar to those obtained with the pthreaded OpenHEVC decoder.

  • Real-Time Lightweight CNN for Detecting Road Object of Various Size

    This paper proposed a novel lightweight convolutional neural network suitable for road object detection which not only for small objects, but for large objects. The proposed network outperformed detection performance of existing convolutional neural networks on KITTI datasets and satisfied real-time processing speed of 10ms on PC and 65ms on NVIDIA TX2. The model is suitable for running in an embedded environment with only 3-million weight parameters.

  • Adaptive reference frame selection for near-duplicate video shot detection

    Near-duplicate video shots provide critical visual link between videos and detecting such video shots efficiently and effectively is of paramount importance in many applications such as detecting copyright infringement. In this paper, we propose an improved near-duplicate video shot detection approach by adaptively selecting reference frames for more effective shot representation. The correlation between adjacent frames is measured with Pearson's Correlation Coefficient (PCC) so that a set of compact yet representative reference frames can be selected adaptively in terms of content variation within video shots. Interest points are further extracted from the selected frames to effectively represent shot contents for similarity matching. Comprehensive experimental results on TRECVID-2008 corpus demonstrate that our proposed approach outperforms the state-of-the-art method effectively.

  • Efficient distortion model based on H.264

    Bused on the study of classic distortion model, Discussed the impact of correlation of video image on the distortion model. According to the distribution of DCT coefficient, a efficient distortion model is proposed which overcomes the shortcoming of the classic distortion model without considering the correlation among pixels.

  • Ownership Identification and Signaling of Multimedia Content Components

    Multimedia content protection is conventionally applied at file level, which cannot cope with the case when the ownership of each media content component is different from each other. And different operations could be expected by different owners when their content components are subjected to unauthorized access. To address these issues, a new method for ownership identification and signaling of content components is proposed for smart media streaming. Prior to streaming, ownership of each media content component is first identified using watermarking or media fingerprinting, then signaled in media presentation description with possible operation list previously decided by its owner. At presentation, each content component will be handled according to the signaling information. Experiments on large datasets demonstrate the efficacy and efficiency of the proposed method.

  • Automatic Feature Subset Selection for Clustering Images using Differential Evolution

    Storing and organizing huge collection of image databases is a challenge for many applications. Such huge collection of images can be organized efficiently using image content clustering. Image Clustering is mapping of images into classes according to their similarity without any prior knowledge. Clustering of images into groups can improve the efficiency of searching images in the database for various web applications. Image content characterization greatly influences the result of clustering. This paper addresses the problem of characterizing and clustering a set of images using Differential Evolution. This work proposes a new algorithm, Automatic Feature Subset Selection for Clustering Images using Differential Evolution (AFSCIDE), to characterize the images with proper selection of textural features by feature subset selection and find groups with clustering using Differential Evolution. Experiments are conducted on various benchmark datasets CUReT, UIUC.

  • Preserving Malay architectural heritage through virtual reconstruction

    Preserving architectural heritage is a challenging and costly task. Digital preservation helps to both reduce costs and make it portable. This paper describes our experience in producing a 3D model of Rumah Tok Su; which is a traditional Malay house, situated in Kedah, Malaysia. The aim of this project is to capture the essence of architectural heritage via still images that are rendered to highlight its beauty and significance.

  • Multiview learning via deep discriminative canonical correlation analysis

    In this paper, we propose Deep Discriminative Canonical Correlation Analysis (DDCCA), a method to learn the nonlinear transformation of two data sets such that the within-class correlation is maximized and the inter-class correlation is minimized. Parameters of the two deep transformations are jointly learned. Unlike CCA and Discriminative CCA, the proposed DDCCA does not need inner product. The proposed DDCCA was evaluated in two applications, handwritten digit recognition and speech-based emotion recognition. The experimental results demonstrated that the proposed DDCCA can get a higher recognition accuracy compared to the existing Deep CCA method.

  • Saliency analysis and region-of-interest extraction for satellite images by biological sparse modeling

    Traditional models for saliency analysis in satellite images cannot genuinely mimic the selection mechanism of human vision system. Furthermore, feature selection needs variant considering the complexity of data distribution of different satellite images thereby not being one-size-fits-all. Aiming at these problems, we propose a novel model based on sparse representation for saliency analysis with biological plausibility and preferably, our model only needs to decide the number of feature without considering feature complexity and massive parameters tuning in other feature learning algorithms. First, sparse filtering is adopted to learn a sparse dictionary for satellite images. Then, we use Incremental Coding Length (ICL) to measure the saliency contribution of every feature for the final saliency map. The region-of- interest (ROI) can be extracted based on saliency maps by thresholding segmentation. Experimental results show that our model achieves better performance compared with several traditional models for saliency analysis and ROIs extraction in satellite images.



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