A great number of Internet of things (IoT) applications rely on real-time communication (RTC) mechanisms for transmission of media. Essentially, applications analyze and process media to make decisions that typically affect actuation and control of embedded devices. IoT networks, however, are subjected to constrains that limit the computational and resource complexity of all entities involved. This

Automatic detection of cyberbullying in social media content is a natural language understanding and generic text classification task. The cultural diversities, country-specific trending topics hash-tags on social media, the unconventional use of typographical resources such as capitals, punctuation, emojis and easy availability of native language keyboards add to the variety and volume of user-generated

Crowd congestion-level analysis (CCA) is one of the most important tasks of crowd analysis and helps to control crowd disasters. The existing state-of-the-art approaches either utilize spatial features or spatial–temporal texture features to implement the CCA. The state-of-the-art deep-learning approaches utilize a single column convolution neural network (CNN) to extract deep spatial features to solve

Visual Object Tracking is a very challenging task because of the large appearance variance caused by illumination, deformation, and motion. Siamese network-based trackers, which select target through a matching function, are widely used for visual object tracking. The trackers are capable of robustly recognizing the target with appearance variance. However, while the filter template is a crucial part

Deep belief networks (DBNs) are used in many applications such as image processing and pattern recognition. But the data vectorized resulting in the loss of high-dimensional data and valuable spatial information. The classical DBNs model is based on restricted Boltzmann machines (RBMs) and full connectivity between the visible units and the hidden units. It requires a large number of parameters to

This research aims to assist users to seek information efficiently while interacting with speech-based information, particularly in multimedia delivery, and reports on an experiment that tested two speech-based designs for communicating multiple speech-based information streams efficiently. In this experiment, a high-rate playback design and a concurrent playback design are investigated. In the high-rate

Nowadays, highly sensitive medical images are vulnerable to data threats and privacy attacks. They must be kept secure while transmitting them across insecure channels precisely for this purpose. The robust image steganography is focused on this work by exploiting Redundant Integer Wavelet Transform (RIWT), Laplacian Pyramid, Arnold scrambling and Histogram shifting algorithm to facilitate secure communication

In this paper, we propose a novel visual object tracking method using a part based appearance model. First, a local kernel feature is developed to encode edge information of patches. Next, bounding box of the target is divided into multiple parts. Then, each part uses correlation filter based tracking to predict position in the next frame. The matrix cosine similarity is utilized to measure reliabilities

Human activity recognition (HAR) is an important branch of human-centered research. Advances in wearable and unobtrusive technologies offer many opportunities for HAR. While much progress has been made in HAR using wearable technology, it still remains a challenging task using unobtrusive (non-wearable) sensors. This paper investigates detection and tracking of multi-occupant HAR in a smart-home environment

Recognition of micro-expressions depends on the key features provided in the form of the temporal information. It needs considerable effort, however, to manually design useful characteristics. Subtle or micro-facial expressions are much difficult than regular facial expressions rich in emotional expressions in a true environment to be identified. An easy solution is discussed in this paper to recognise

Denigration is a specialized form of cyberbullying which describes a recurrent, sustained and intentional attempt to damage the victim’s reputation or ruin the friendships that he or she has by spreading unfounded gossip or rumors online. It is the most common bullying tactic involving character assassination of public figures like celebrities and politicians. As a comprehensive approach to match to

Nowadays, with the development of social media networks, micro-videos, an emerging form of user-generated contents (UGCs), are gradually attracting greater interest. Some of them are widely spread, while others draw little attention. The popular micro-videos have significant commercial potential in many ways, such as online advertising and bandwidth allocation. In recent years, the popularity prediction

A stereo visual odometry algorithm based on the fusion of optical flow tracking and feature matching called LK-ORB-SLAM2 was proposed. In LK-ORB-SLAM2, the operation of optical flow tracking is introduced to adjust the intensive and time-consuming operation of feature matching. This requires solving a key issue: how to solve the problem of losing feature points during optical flow tracking. For this

Plant recognition is a meaningful research that has attracted many researchers. Due to the variety of plants, it is difficult for the existing identification methods to identify their species efficiently. We proposes a plant recognition method based on Jaccard distance and Bag of words (BOW). Firstly, Jaccard distance is employed to calculate the similarity between the test sample and part of the training

Thermal sensors bring a lot of benefits for object tracking due to the robustness to lighting changes over time, which still give a great difficulty to traditional tracking methods. Despite this powerful advantage, the ambiguity due to background clutters and occlusions makes the problem of thermal sensor-based tracking intractable. In this paper, we propose a novel framework for multiple object tracking

The Flexible Dual TCP-UDP Streaming Protocol (FDSP) combines the reliability of TCP with the low latency of UDP, thus providing transport layer improvements towards maintaining high QoE of multi-bitrate videos in adaptive streaming. FDSP delivers the more critical parts of the video data via TCP and the rest via UDP. FDSP also uses Bitstream Prioritization (BP), a sliding scale that determines the

The text to speech technology has achieved significant progress during the past decade and is an active area of research and development in providing different human–computer interactive systems. Even though a number of speech synthesis models are available for different languages focusing on the domain requirements with many motive applications, a source of information on current trends in Indian

Visual media has become one of the most potent means of conveying opinions or sentiments on the web. Millions of photos are being uploaded by the people on famous social networking sites for expressing themselves. The area of visual sentiment analysis is abstract in nature due to the high level of biasing in the human recognition process. This work proposes a residual attention-based deep learning

Skewness and obliqueness of vehicle plate images influence license plate recognition. The more tilted plate images are, the harder the recognition task is. To this end, if plate images are preprocessed to be aligned and rectified, the recognition performance would improve. We propose deep neural network models that can locate four corner plate positions, which can then be used to perform the perspective

We propose a novel method for modeling crowd video dynamics by adopting a two-stream convolutional architecture which incorporates spatial and temporal networks. Our proposed method cope with the key challenge of capturing the complementary information on appearance from still frames and motion between frames. In our proposed method, a motion flow field is obtained from the video through dense optical

The preferences of Web information purchasers are changing. Cost-effectiveness (i.e., an emphasis on performance with respect to price) is becoming less regarded than cost-satisfaction, which emphasizes the purchaser’s psychological satisfaction. A method to improve a user’s cost-satisfaction in recommending multimedia content is to use the mood-inherent in multimedia items. An example of applications

It is an extremely interesting work to understand the minority costumes in computer vision and ethnology community. It explored some crucial clue for understanding minority costumes via computer vision technology. As it known to all, complicated and subtle structure between different minority costumes lead it becomes hard work to recognize them with computer vision even people. An intelligent framework

TV advertisements are less and less watched as most viewers turn their attention to the smartphone during commercial breaks. Therefore, broadcasters are facing a novel challenge: how to improve the engagement between viewers and TV commercials. In this paper, we investigate whether gamification can be a winning strategy. Indeed, despite some strategies that have recently been proposed (e.g., cross-media

Human activity recognition has been a significant goal of computer vision since its inception and has developed considerably in the last years. Recent approaches to this problem increasingly favour the use of data-driven deep learning methods. To facilitate the comparison of these methods, several datasets pertaining to labelled human activity have been created, having great variation in content and

Along with the growth of the internet, the number of information published increased exponentially. This huge flow of information causes a problem called “information overload” which makes it harder for internet users to find key information they needed on the internet. To solve this, this paper proposes an application that helps user find trending news of their query/interest easily. Some challenges

In data encryption, recently commonly used schemes are chaos-based due to their properties of sensitivity to initial conditions, control parameters, and pseudo-randomness. The chaotic crypto-algorithms are appropriate for extensive data encryption for images, audio or videos. In this paper, a novel audio encryption algorithm based on substitution and permutation network is proposed. In this study,

Package RMoCap is an advanced open-source tool for scientists, engineers and computer graphics familiar with R language who work with motion capture (MoCap) technology. Package provides them with MoCap data handling, statistical processing, visualizing and analysis. Package uses well-established MoCap file exchange format and can be easily integrated with most of the motion analysis workflows. Among

Under the premise of ensuring good speech quality and resistance to steganalysis, how to embed as much information as possible into low-bit-rate speech is a challenge. The existing research mainly focuses on least significant bits in the compressed speech streams or line spectral frequencies in the encoding processes of the G.723.1 and G.729a codecs. In this paper, we are concentrating on steganography

With the recent advent of three-dimensional (3D) sound home theater systems (HTS), more and more TV viewers are experiencing rich, immersive auditory presence at home. In this paper, visual processing approaches are provided to make 3D audio–visual (AV) systems more realistic to the viewers. In the proposed system, a visual engine processes stereo video streams to extract a disparity map for each pair

As the VoIP steganographic methods provide a low capacity covert channel for data transmission, an efficient and real-time data transmission protocol over this channel is required which provides reliability with minimum bandwidth usage. This paper proposes a micro-protocol for data embedding over covert storage channels or covert hybrid channels developed by steganographic methods where real-time transport

Image stitching, or known as image mosaic, is the process that combines images with overlapped areas to form an image with wide view and high resolution. Image stitching technique has been quickly developed these years. It has become an important branch in digital image processing and has wide applications. Many image stitching methods have been proposed. This article takes investigation on some image

With the advancement of time, the computer vision systeams are focusing on mimicking the human visual system. In this manuscript, we tried to develop a model which works at improving both the detection accuracy and computation time. First, two double opponent color based features and twelve directional edge features using Gabor filter are computed. Then the most dominant feature pertaining to the salient

Schizophrenia, a serious psychological disorder, causes auditory and visual hallucinations, and delusions in a person. Several studies have shown that schizophrenia imposes structural changes in human brain. Relative changes in the grey matter volume of the schizophrenia patients in comparison to healthy controls have been well explored. However, identification of relevant brain regions that exhibit

In order to realize the secure transmission of the H.264 compressed video bitstream, a detailed analysis of the structure for video bitstream is performed. The parameter set and frame header data related to video decoding are retained, and the slice data payload in the network abstraction layer unit is selected as the encryption object. The video format is compliant under the premise of real time and

Under the background of contemporary cultural protection and dynamic inheritance, the interpretation and re-expression of the artistic connotations of Chinese literati paintings have become the main direction of heritage research. Digital technology and multimedia expression have become important means of cultural expression and transmission. Most Chinese literati paintings are ink paintings, and the

While much research has been devoted to algorithm improvement of the machine learning model for multimedia applications, relatively little research has focused on the acquisition of massive multimedia datasets with strict data demands for model training. In this paper, we propose a Quality-of-Information (QoI) aware incentive mechanism in multimedia crowdsensing, with the objective of promoting the

Since the distinction between two expressions is fairly vague, usually a subtle change in one part of the human face is enough to change a facial expression. Most of the existing facial expression recognition algorithms are not robust enough because they rely on general facial features or algorithms without considering differences between facial expression and facial identity. In this paper, we propose

Aiming at the problem of 3D point cloud noise affecting the efficiency and precision of human body 3D reconstruction in complex scenes, a 3D point cloud registration denoising method for human motion image using depth learning algorithm is proposed. First, two Kinect sensors are used to collect the three-dimensional data of the human body in the scene, and the spatial alignment under the Bursa linear

Abstract Original medical images are often inadequate for clinical diagnosis. Certain prior information can be used as an important basis for disease diagnosis and prevention. In this study, an oriented grouping-constrained spectral clustering method, OGCSC, is proposed to deal with medical image segmentation problems. OGCSC propagates the group information from the affinity matrix and subdivides the

Abstract Representing image sets and videos with Grassmann manifold has become popular due to its powerful capability to extract discriminative information in machine learning research. However, existing techniques operations on Grassmann manifold are usually suffering from the problem of computational expensive, thus the application range of Grassmann manifold is limited. In this paper, we propose

Abstract To improve the image-processing accuracy and speed of laser three-dimensional imaging system, effectively filter the noise in the image, and effectively optimize the processing speed and image accuracy, this paper proposes an improved adaptive mean-shift image-filtering algorithm based on the traditional mean-shift-filtering algorithm. First, this paper introduces the traditional mean-shift-filtering

With the massive use of images over the Internet, the security of some of them has become critical. One of the most used encryption algorithms is AES. Although this algorithm provides high security for text data, it is not suitable for images in view of their characteristics including correlation and redundancy. To have a more suitable and efficient algorithm for the encryption of images, we have deeply

RGB-D sensors have been in great demand due to its capability of producing large amount of multimodal data like RGB images and depth maps, useful for better training of deep learning models. In this paper, a deep learning model for recognizing human activities in a video sequence by combining multiple CNN streams has been proposed. The proposed work comprises the use of dynamic images generated from

Owing to the rapid development and advancements in the field of networks and communication, sharing of multimedia contents over insecure networks has become vital. The confidentiality of audio signals is predominantly needed in military and intelligence bureau applications. The proposed algorithm addresses this issue by encrypting audio signal using chaotic maps in spatial and transform domain. Discrete

In this paper, we propose a proximity-based indoor positioning system which is capable of monitoring mobile device user’s indoor locations where the commonly used GPS signal is unavailable or weak. The designed system is aimed to be integrated into a context-aware communications system to prevent transmission of irrelevant content to all users but easing delivery of the location-based information.

Abstract Solid-state disks (SSDs) are now being used as enterprise storage servers owing to their technical merits such as low power consumption, shock resistance, and excellent random read performance. To handle the large storage requirements for video data, they can be used as a cache for hard disk drives (HDDs) in video servers, but this poses several questions such as (1) which video segments can

With advancement of various information processing and storage techniques, the scale of digital music collections has been growing at very fast speed during recent decades. To support high-quality content-based retrieval over such a large volume of music data, how to develop indexing structure with good effectiveness, efficiency and scalability becomes an important research issue. However, existing

Abstract Ubiquitous multimedia applications diffuse our everyday life activities which appreciate their significance about improving our experiences. Therefore, proliferation of the multimedia applications enhancing these experiences needs critical attention of the researchers. Considering this motivation, to overcome the possible barrier of the proliferation of the 3D video-related multimedia applications

Recently, research interests have been paid for using recurrent neural network (RNN) as the decoder in video captioning task. However, the generated sentence seems to “lose track” of the video content due to the fixed language rule. Though existing methods try to “guide” the decoder and keep it “on track”, they mainly rely on a single-modal feature that does not fit the multi-modal (visual and semantic)

With the development of 3D model reconstruction, manufacturing, and 3D model vision technologies, 3D model recognition has attracted much attention recently. To handle the 3D model recognition problem, in this paper, we propose a panorama based on multi-channel-attention (MCA) CNN network for the representation of the 3D model. The proposed method is composed of three parts: extracting views, transform

Abstract As an important format of multimedia, music has filled almost everyone’s life. Automatic analyzing of music is a significant step to satisfy people’s need for music retrieval and music recommendation in an effortless way. Thereinto, downbeat tracking has been a fundamental and continuous problem in Music Information Retrieval (MIR) area. Despite significant research efforts, downbeat tracking

Abstract This article proposes a new method for subjective 3D video quality assessment based on crowdsourced workers—Crowd3D. The limitations of traditional laboratory-based grade collection procedures are outlined, and their solution through the use of a crowd-based approach is described. Several conceptual and technical requirements of crowd-based 3D video quality assessment methods are identified

Stereoscopic devices are becoming more popular every day. The 3D visualization that these displays offer is being used by videogame designers to enhance the user’s game experience. Autostereoscopic monitors offer the possibility of obtaining this 3D visualization without the need for extra device. This fact makes them more attractive to videogame developers. However, the configuration of the cameras

Owing to the rise of living standard, people attach greater importance to personal appearance, especially clothes matching. With image processing and machine learning technology, we can analyze the pattern of clothes matching for recommendation on clothes images. However, we still face great challenges. To be more specific, there exist excessive complicated factors influencing relation among clothes

Abstract It is becoming increasingly difficult to find a particular app on a smartphone due to the increasing number of apps installed. Consequently, it is important to be able to quickly and accurately predict the next app to be used. Two problems arise in predicting next-app usage from the app usage history. One is that some algorithms do not consider the increasing amount of training data available

Keyframe extraction plays a significant role in wide variety of real-time video processing applications such as video summarization, video management and retrieval, etc. A keyframe captures the whole content of its shot and does not contain any redundant information. The keyframe extraction algorithms are facing challenges due to different visual characteristics in videos of different categories. Therefore

Occlusion is an important factor for analysis of human gait recognition in real-time scenarios. In multi-person gait (MPG) or dynamic occlusion, gait recognition is affected due to occluded body parts known as region of interests (ROIs). The aim of this article is to reconstruct the occluded ROIs and measure the errors associated with the reconstruction methods. The contribution of this article is