Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

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

Abstract 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,

Abstract 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

Abstract 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

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 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

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

Abstract 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

Abstract 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

Abstract 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

Abstract 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

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

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