Video Management Research Articles

Vid2U: Facilitating Students’ Learning Through Video Annotation for Tablet Device

Electronic learning (e-learning) applications are widely used in the Higher-Education institutions to deliver and share learning contents among the students. However, most of the e-learning applications are developed for offline or online desktops. Mobile learning (m-learning) is introduced to allow learners to experience the learning opportunities via mobile devices such as handheld computers, MP3 players, notebooks, mobile phones, and tablets. Interactive video refers to a technique which allows users to have some interactions with the media instead of watching a static video. One of the many ways of making video having the interactive elements is through video annotation. Although the use of video annotation is quite common in learning, there are still needs for more efforts on designing annotation facilities for video management in mobile learning environment. Apart from that, the application of video annotation on mobile devices is also still in its infancy, especially for recent devices like iPad, Microsoft Surface, Samsung Galaxy Tab, and others. The objective of the proposed mobile learning application, Vid2U is to provide the flexibility of accessing and managing video materials at anywhere and anytime, making learning even more widely available. The Vid2U is equipped with many functions such as allowing students to view lecture videos and other video materials related to the course when absent from classes. Students can also add, edit, and delete their lecture notes based on the lecture videos. The mobile-based application also allows students to search video materials related to all courses taken by them. Experimental results obtained from surveys have shown that the Vid2U is able to provide better learning environment for the university learners, which lead to a deeper level of learning engagement.

A fault-tolerant ONVIF protocol extension for seamless surveillance video stream recording

ONVIF (Open Network Video Interface Forum) is an importance industrial standard for the video surveillance field. There are over 8000 ONVIF-compliant IP cameras (i.e., ONVIF NVT) and network video recorders (i.e., ONVIF NVS) from various vendors listed on the ONVIF official website. However, because the current ONVIF specifications do not support any fault-tolerant functions to handle NVS failure, in this paper we propose a fault-tolerant solution for ONVIF NVS and try to minimize the modifications to the current ONVIF specifications in the proposed design. Besides, we also propose an extension to the ONVIF NVT for preventing the loss of captured NVT video data during the failover procedure triggered by NVS failure. Finally, we evaluate the following four performance metrics of the proposed fault-tolerant ONVIF surveillance system: the maximal video local cache time supported by an NVT, the response time for accessing an ONVIF web service, the interrupt duration of video recording due to NVS failure, and the live video black out time observed by a video management system. Since the experimental results are all within the acceptable range for a real fault-tolerant video surveillance system in the real world, the experiences provided by this paper is a good reference for improving the fault-tolerant capabilities of the ONVIF video surveillance systems.

Motion sketch based crowd video retrieval

Crowd video retrieval with desired motion flow segmentation is an important problem in surveillance video management, e.g., video indexing and browsing, especially in the age of big data. In this paper, we address this issue from the motion-level perspective by using hand-drawn sketches as queries. Motion sketch based crowd video retrieval naturally suffers from challenges in crowd motion representation and similarity measurement. To tackle them, we propose to (1) leverage the motion structure coding algorithm for motion-level video indexing and hand-drawn sketch representation and (2) exploit distance metric fusion strategy incorporated with Ranking SVM for measuring the relevant degree between a sketch query and crowd videos. Specifically, for video indexing, motion decomposition is utilized to separate sub-motion vector fields with typical patterns from a set of optical flows. Then, the motion-level descriptors of the vector fields are computed and stored in an index database. To represent motion sketches, we propose a mechanism by vectorizing the sketches followed by motion structure coding. In the retrieval stage, we first compute the pairwise distance with different metrics between a new sketch query and crowd videos, and then stack them into a feature vector as the input of the Ranking SVM algorithm. Finally, we use the learned retrieval model to predict the ranking score of each crowd video in the database. Experimental results on the publicly available crowd datasets show the robustness and effectiveness of the proposed sketch based crowd video retrieval system.

Energy-aware cache hierarchy assessment targeting HEVC encoder execution

This article presents a framework for assessing the behavior and energy impact of cache hierarchies when encoding HEVC on general-purpose processors. The memory energy estimation framework estimates energy consumption of cache hierarchies based on mathematical models combined with memory access profiling tools. The energy analysis of several cache hierarchies targeting HEVC encoders with different input parameters is also carried out. This article provides relevant information on the energy consumption of HEVC encoders by taking into account the different tradeoffs between energy efficiency, coding efficiency, and other important cache memory design parameters, such as miss rates and access latency. The first analysis explores cache performance for different specifications, such as capacity, line size. Results show that most of the energy is spent on reading operations (almost 73% on the first level cache), indicating that HEVC encoders could benefit from memory technologies with low reading energy costs. This analysis also pointed that increasing the capacity affects more the energy performance of the first level cache, which represents 34.78% (on average) more energy consumption than the last level cache. Based on this investigation, we report the most suited cache specifications for HEVC encoders for each video resolution. The second analysis discusses the impact of HEVC input parameters in cache performance, demonstrating that it is possible to save up to 30% of energy with a small increase of 2% in BD-BR. A comparative analysis between HM (HEVC model) and x265 (H.265 video codec) HEVC software models is presented, demonstrating that x265 is faster (speedup to 648x), and more cache efficient providing less memory energy (31.38% on average) compared to the HM implementation. The results obtained with the proposed framework indicate that the management of video encoding parameters combined with application-tuned cache specifications has a high potential to reduce energy consumption of video coding systems while keeping video quality.

Novel robust zero-watermarking scheme for digital rights management of 3D videos

Digital watermarking is an effective technique for the digital rights management (DRM) of three-dimensional (3D) videos, which is still a crucial issue in the field of 3D televisions. The current watermarking schemes for 3D videos can be classified into two main categories: One embeds watermarks into 2D video frames, and the other embeds watermarks into depth maps. The former causes irreversible distortions to synthesized 3D videos whereas the latter is insufficiently robust against some of normal video attacks. Moreover, because these watermarking schemes only embed watermarks into either 2D video frames or depth maps of 3D videos, none of them can protect the copyrights of these two parts simultaneously and independently. To address those problems, a novel robust zero-watermarking scheme for the DRM of 3D videos is proposed in this study. In the proposed scheme, master shares are first generated by extracting features from temporally informative representative images (TIRIs) of both the 2D video frames and depth maps. Then, ownership shares, which denote the relationships between copyright information and master shares, are generated based on the Visual Secret Sharing (VSS) scheme and stored for copyright identification. Finally, copyright ownerships are identified by stacking master shares and ownership shares. The experiment results demonstrate that the proposed scheme outperforms the current state-of-the-art watermarking schemes because it does not cause any distortion to the synthesized 3D videos, exhibits strong robustness against various video attacks, and protects the copyrights of 2D video frames and depth maps of 3D videos simultaneously and independently.

Construction and Application of MOOC-based College English Micro Lesson System

this paper aims to introduce the construction and application of MOOC-based micro lesson system in college English teaching. Micro lesson, as a new type of curriculum resource, has injected new vitality into the development of education. College English micro lesson teaching and learning system, based on MOOC concept, multimedia cognition theory and micro lesson pattern, can be constructed to realize the learner-centered multiple interaction and teachers’ unified management of micro lesson video, so as to greatly improve the creativity and effectiveness of college English teaching & learning activity.

Editorial

During this year’s IASA conference in Washington, DC at the Library of Congress, I noticed continued discussion of trends that are ever-looming in our feld: (1) digital video care and management improvements and (2) increased access demands for digital audiovisual collections. We are required to be agile in our ability to provide effortless access to audiovisual archives in the digital landscape; and simultaneously, we are challenged to design long-term storage infrastructure for the preservation of exponentially growing collections of the biggest (in terms of bytes) digital content in existence—high defnition digital audio and digital video objects. At the core of our work, while we are attending to the many details of audiovisual archives, most of us are still laying dependable infrastructure for digital preservation of and versatile access to our ever-growing digital archives. This is the reality in which we operate today.

멀티 홉 Wi-Fi Direct 통신 기반 실시간 영상관리 시스템 성능 분석

지진, 홍수, 태풍 등의 자연 재해 및 화재, 테러 등 재난 발생시 현장 상황의 영상을 촬영하여 지휘본부에 위치한 서버에 전송하여 현장상황을 한 눈에 파악할 수 있게 하는 영상관리시스템이 요구된다. 본 논문에서는 영상관리시스템 구축에 필요한 성능 요소 정보를 파악하기 위해 와이파이 다이렉트 통신 기반의 애드혹 망 구성 방법을 제시하고 영상관리시스템에 대한 환경 구축을 통해 성능을 평가하였다. 평가한 성능 시험항목은 '영상 압축률 및 영상 크기에 따른 패킷 흐름 시험', '거리에 따른 패킷 흐름 및 트래픽 시험', 'LOS(Line of Sight) 여부에 따른 패킷 흐름 시험', '시나리오 성능 시험'이다. When disasters such as earthquake, flood, typhoon, fire and terrorism are occurred a video management system is required which can shoot video on the disaster site, and send it to a server located in the command center that can grasp at a glance the site conditions. In this paper, to know the performance elements information needed to construct the video management system. we presented a method of configuring an ad hoc network based on Wi-Fi direct communication. And we also evaluated the performance through built of environment for the video management system. The evaluated performance test items are 'packet flow tests according to the video compression ratios and the image sizes', 'packet flow tests according to the distance and traffic tests', 'packet flow tests according to whether LOS or not', and 'performance test of scenarios'.

Panopto with Moodle: Enabling videos and screencasts to be effective assessment tools for all

The widespread availability in universities of modern video recording and management systems integrated into Virtual Learning Environments, such as Panopto with Moodle, now enables all students to easily create and submit their own recordings for assessment, and the platform enables the management of the marking and feedback to be simple and effective. It is time that lecturers embraced this development in order that assessment remains effective and relevant. The ability to create a screencast or video for assessment should be an essential digital literacy skill for all university students.

Video Management and Resource Allocation for a Large-Scale VoD Cloud

We consider providing large-scale Netflix-like video-on-demand (VoD) service on a cloud platform, where cloud proxy servers are placed close to user pools. Videos may have heterogeneous popularity at different geo-locations. A repository provides video backup for the network, and the proxy servers collaboratively store and stream videos. To deploy the VoD cloud, the content provider rents resources consisting of link capacities among servers, server storage, and server processing capacity to handle remote requests. We study how to minimize the deployment cost by jointly optimizing video management (in terms of video placement and retrieval at servers) and resource allocation (in terms of link, storage, and processing capacities), subject to a certain user delay requirement on video access. We first formulate the joint optimization problem and show that it is NP-hard. To address it, we propose Resource allocation And Video management Optimization (RAVO), a novel and efficient algorithm based on linear programming with proven optimality gap. For a large video pool, we propose a video clustering algorithm to substantially reduce the run-time computational complexity without compromising performance. Using extensive simulation and trace-driven real data, we show that RAVO achieves close-to-optimal performance, outperforming other advanced schemes significantly (often by multiple times).

Event-based media processing and analysis: A survey of the literature

Research on event-based processing and analysis of media is receiving an increasing attention from the scientific community due to its relevance for an abundance of applications, from consumer video management and video surveillance to lifelogging and social media. Events have the ability to semantically encode relationships of different informational modalities, such as visual–audio–text, time, involved agents and objects, with the spatio-temporal component of events being a key feature for contextual analysis. This unveils an enormous potential for exploiting new information sources and opening new research directions. In this paper, we survey the existing literature in this field. We extensively review the employed conceptualization of the notion of event in multimedia, the techniques for event representation and modeling, the feature representation and event inference approaches for the problems of event detection in audio, visual, and textual content. Furthermore, we review some key event-based multimedia applications, and various benchmarking activities that provide solid frameworks for measuring the performance of different event processing and analysis systems. We provide an in-depth discussion of the insights obtained from reviewing the literature and identify future directions and challenges.

Managing construction schedule by telepresence: Integration of site video feed with an active nD CAD simulation

Abstract In recent years, the increased utilization of building information modeling (BIM) has brought attention to the need for BIM-based operation systems that provide a decision-making feature in addition to visual information. This study constructed a project schedule management system that integrates the data points of an nD computer-aided design (CAD) object (e.g., schedule and resource information) with a telepresence concept video management operation system. A methodology was developed that allows the user to monitor the current construction status relative to the design and verify the completion of the facility through real-time comparison between the planned process represented by the nD object and the actual image of the construction site sent from an on-site webcam. An active nD CAD system was developed that possesses features such as a comparative simulation between the on-site image and a 4D object to minimize interference between processes and a 5D object that is specialized to the resource mobilization level of the field. A telepresence-based nD CAD system was developed based on this methodology, and the practicality of the system was verified by webcams installed on a bridge construction site. Thus, the project manager is not only able to utilize the nD object for visualization but is also able to use the system as a decision-making system to formulate the most appropriate project schedule by comparing the nD object with the actual on-site image.

A pattern-based evaluation of download and cache management algorithms for annotated interactive non-linear videos

With modern technologies, it is possible to create annotated interactive non-linear videos (a form of hypervideo) for the Web. These videos have a non-linear structure of linked scenes to which additional information (other media like images, text, audio, or additional videos) can be added. A variety of user interactions—like in- and between-scene navigation or zooming into additional information—are possible in players for this type of video. Like linear video, quality of experience (QoE) with annotated hypervideo experiences is tied to the temporal consistency of the video stream at the client end—its flow. Despite its interactive complexity, users expect this type of video experience to flow as seamlessly as simple linear video. However, the added hypermedia elements bog playback engines down. Download and cache management systems address the flow issue, but their effectiveness is tied to numerous questions respecting user requirements, computational strategy, and evaluative metrics. In this work, we (a) define QoE metrics, (b) examine structural and behavioral patterns of interactive annotated non-linear video, (c) propose download and cache management algorithms and strategies, (d) describe the implementation of an evaluative simulation framework, and (e) present the algorithm test results.

Efficient indexing and retrieval of large-scale geo-tagged video databases

We are witnessing a significant growth in the number of smartphone users and advances in phone hardware and sensor technology. In conjunction with the popularity of video applications such as YouTube, an unprecedented number of user-generated videos (UGVs) are being generated and consumed by the public, which leads to a Big Data challenge in social media. In a very large video repository, it is difficult to index and search videos in their unstructured form. However, due to recent development, videos can be geo-tagged (e.g., locations from GPS receiver and viewing directions from digital compass) at the acquisition time, which can provide potential for efficient management of video data. Ideally, each video frame can be tagged by the spatial extent of its coverage area, termed Field-Of-View (FOV). This effectively converts a challenging video management problem into a spatial database problem. This paper attacks the challenges of large-scale video data management using spatial indexing and querying of FOVs, especially maximally harnessing the geographical properties of FOVs. Since FOVs are shaped similar to slices of pie and contain both location and orientation information, conventional spatial indexes, such as R-tree, cannot index them efficiently. The distribution of UGVs' locations is non-uniform (e.g., more FOVs in popular locations). Consequently, even multilevel grid-based indexes, which can handle both location and orientation, have limitations in managing the skewed distribution. Additionally, since UGVs are usually captured in a casual way with diverse setups and movements, no a priori assumption can be made to condense them in an index structure. To overcome the challenges, we propose a class of new R-tree-based index structures that effectively harness FOVs' camera locations, orientations and view-distances, in tandem, for both filtering and optimization. We also present novel search strategies and algorithms for efficient range and directional queries on our indexes. Our experiments using both real-world and large synthetic video datasets (over 30 years' worth of videos) demonstrate the scalability and efficiency of our proposed indexes and search algorithms.

SIVA suite

The SIVA Suite is an open source framework for the creation, playback, and administration of hypervideos. Allowing the definition of complex navigational structures, our hypervideos are well suited for different scenarios. Compared to traditional linear videos, they especially excel in e-learning and training situations (see [1] and [2]), where fitting the teaching material to the needs of the viewer can be crucial. Other fields of application include virtual tours through buildings or cities, sports events, and interactive video stories. The SIVA Suite consists of an authoring tool (SIVA Producer), an HTML5 hypervideo player (SIVA Player), and a Web server (SIVA Server) for user and video management. It has been evaluated in various scenarios with several usability tests and has been improved step-by-step since 2008.

An Object of Interest based Segmentation Approach for Selective Compression of Video Frames

The automatic segmentation of objects of interest is a new research area with applications in various fields. In this paper, the object segmentation method is used for content based video management and compression of video frames for video conferencing. The face region, which is the object of interest in the video frames, is identified first using a skin color based algorithm. The face regions are then extracted and encoded without loss, while the nonface regions and the non-face frames are quantized before encoding. Results show that the decompressed video has an improved quality with the proposed approach at low bit rates.

Quality Increase of Viral Video Management on the basis of Synergetic Approach

The article considers one of the modern methods for marketing communication – viral marketing. Users of social networks act simultaneously as a target audience and distributors (recipients) of viral video. It is suggested that users should be segmented into three basic groups: Active, interested and passive. Concentration of these types of recipients in the network determines possible scenarios of self-development of viral video: Death, survival, transformation, each scenario being characterized as a field of attractors of virus development with dying out rate, stability level and growth rate inherent in it. Dynamic and statistical indicators are proposed for assessment of virus efficiency (increase of viewings, increase of users), on the basis of which the matrix of current states of viral video is built. A methodology is proposed for assessment of the current and the future states of the virus in accordance with statistics of indicators for the previous period based on the linear regression method. Limit values of coefficients of users and video viewing increase, which corresponds to various scenarios of virus development, including instability states, are defined. The possibility of diagonal express-assessment of the matrix when the number of users and number of viewings are believed to be conditionally equal is reviewed and practically trialed.

A framework for video transcoding and management in cloud manufacturing

Cloud-based manufacturing has been defined as CMfg. It is a system built on cloud computing technology that can integrate a large number of manufacturing resources. In a CMfg system, there are huge amounts of data and one of them is the video used to monitor manufacturing processes and learn knowledge. In cloud platform, the video data generate fast and have diverse formats, so the need for unified transcoding and management is necessary. In this article, an elastic cloud framework for fast video transcoding process and management is proposed. The core of this framework is a distributed system based on Hadoop that is designed for massive data storage and parallel computing.

The National Capital Region closed circuit television video interoperability project.

The National Capital Region (NCR) includes many government jurisdictions and agencies using different closed circuit TV (CCTV) cameras and video management software. Because these agencies often must work together to respond to emergencies and events, a means of providing interoperability for CCTV video is critically needed. Video data from different CCTV systems that are not inherently interoperable is represented in the "data layer." An "integration layer" ingests the data layer source video and normalizes the different video formats. It then aggregates and distributes this video to a "presentation layer" where it can be viewed by almost any application used by other agencies and without any proprietary software. A native mobile video viewing application is also developed that uses the presentation layer to provide video to different kinds of smartphones. The NCR includes Washington, DC, and surrounding counties in Maryland and Virginia. The video sharing architecture allows one agency to see another agency's video in their native viewing application without the need to purchase new CCTV software or systems. A native smartphone application was also developed to enable them to share video via mobile devices even when they use different video management systems. A video sharing architecture has been developed for the NCR that creates an interoperable environment for sharing CCTV video in an efficient and cost effective manner. In addition, it provides the desired capability of sharing video via a native mobile application.

Traffic Management of Video on Demand: An Analysis of Investments for Improving the End User's Quality of Experience

The current escalation in user demand for web contents, particularly Video on Demand (VoD), is causing a continuing increase in both the types of web traffic and the volumes of data transmitted. The greater demand arises from the new means of communication employed by individuals and companies, as well as the development of readily usable applications distributed by ‘app stores’. In this paper, we suggest that the stakeholders of a VoD framework, the Content Providers (CPs) and the Internet Service Providers (telcos/ISPs), should guarantee a solid Quality of Experience (QoE) to the end user through two potential investments: either in ultra-broadband (UBB) or in the technologies for the acceleration of web content, known as the Content Delivery Network (CDN) and Transparent Internet Caching (TIC). The aim of the paper is to analyse these investments in terms of providers' profits. The base hypothesis is that the investments are subsidized by the CPs, which, in recent years, have indeed been directing a large part of their revenues towards investments in network infrastructure.