Promoting student learning with online videos : a research agenda

Gen Y students are digital natives (Prensky 2001) who learn in complex and diverse ways, with a variety of learning styles apparent in any given course. This paper proposes a web 2.0 conceptual learning solution–online student videos–to respond to different learning styles that exist in the classroom.

Bitrate modeling of scalable videos using quantization parameter, frame rate and spatial resolution

The quality and bitrate modeling is essential to effectively adapt the bitrate and quality of videos when delivered to multiplatform devices over resource constraint heterogeneous networks. The recent model proposed by Wang et al. estimates the bitrate and quality of videos in terms of the frame rate and quantization parameter. However, to build an effective video adaptation framework, it is crucial to incorporate the spatial resolution in the analytical model for bitrate and perceptual quality adaptation. Hence, this paper proposes an analytical model to estimate the bitrate of videos in terms of quantization parameter, frame rate, and spatial resolution. The model can fit the measured data accurately which is evident from the high Pearson correlation. The proposed model is based on the observation that the relative reduction in bitrate due to decreasing spatial resolution is independent of the quantization parameter and frame rate. This modeling can be used for rate-constrained bit-stream adaptation scheme which selects the scalability parameters to optimize the perceptual quality for a given bandwidth constraint.

Multi-modal summarization of key events and top players in sports tournament videos

To detect and annotate the key events of live sports videos, we need to tackle the semantic gaps of audio-visual information. Previous work has successfully extracted semantic from the time-stamped web match reports, which are synchronized with the video contents. However, web and social media articles with no time-stamps have not been fully leveraged, despite they are increasingly used to complement the coverage of major sporting tournaments. This paper aims to address this limitation using a novel multimodal summarization framework that is based on sentiment analysis and players' popularity. It uses audiovisual contents, web articles, blogs, and commentators' speech to automatically annotate and visualize the key events and key players in a sports tournament coverage. The experimental results demonstrate that the automatically generated video summaries are aligned with the events identified from the official website match reports.

Exploration and optimization of user experience in viewing videos on a mobile phone

Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user’s viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user’s acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanying the quantitative method (acceptance assessment), we used a qualitative interview method to obtain a deeper understanding of a user’s assessment criteria and to support the quantitative results from a user’s perspective. Based on the results from data analysis, we advocate two user-driven strategies to adaptively provide an acceptable quality and to predict a good user experience, respectively. There are two main contributions from this paper. Firstly, the field user study allows a consideration of more influencing factors into the research on user experience of mobile video. And these influences are further demonstrated by user’s opinions. Secondly, the proposed strategies — user-driven acceptance threshold adaptation and user experience prediction — will be valuable in mobile video delivery for optimizing user experience.

Adaptive bilateral filtering using saliency map for deblocking low bit rate videos

This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.

Automatic region-of-interest detection and prioritisation for visually optimised coding of low bit rate videos

The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.

The platform of spoof videos : The case of Tudou.com

This paper analyses the enabling and constraining role of platforms in the development of online video-spoofing culture in China. Using Tudou.com, one of China’s most popular video-sharing sites, as a case study, the paper discusses how video-sharing sites facilitate and curtail the self, and how they negotiate and balance among users, clients and the state, teasing out the complex politics of platforms in China. Particular reference is made to three “star users”, Jiaoshou, Hu Ge and Corndog, who gained fame for themselves via the popularity of their spoof videos on this platform.

Seriously playful : the uses of networked spoof videos in China

This thesis examines online spoof videos in China. It shows the relationship between user-created content and change and how such videos are impacting on social memory. In the West, we are witnessing two outstanding trends in media. On the one hand, media are turning more "demotic" (Turner, 2006) and "participatory" (Jenkins, 2006), whereby lay audiences use popular media for identity formation, representation and association, reconfiguring the media and cultural landscape, and rendering invalid the old paradigm based on the dichotomy of audience and author, creator and consumer, expert and amateur. On the other hand, in both mainstream media and user-creation online there is a trend towards "silly citizenship", with comedy, send-ups and spoofs that used to reside in the margin propelled to the central stage in both pleasure and politics (Hartley, 2010), as is shown in the rising popularity of the Daily Show, Colbert Report, and spoof videos in elections ,e.g. the 2008 presidential election in US (Gray, Jones, & Thompson, 2009; Tryon, 2008). User generated content—and spoof subcultures—is now much a debated phenomenon in China. However, with different political (one party rule and censorship) and cultural (media regarded mainly as instrument for education and social stabilization instead of a critical fourth estate) configurations, will the social and cultural impacts of the two trends in the West be as the same in China? If not, what will be the specificities in the China context? The project starts with a historical review of popular culture and user-created content in China, before turning to spoof videos and looking at how they are produced and shared, travel and diffused on the Internet, and how the communities and sub-cultures forming and emerging around spoof videos are changing the overall cultural landscape in China. By acting as a participant observer in online video sharing sites and conducting face-to face as well as online interviews, I identify lead users and creators of spoof videos and the social networks emerging around them. I call these lead users "skill hubs" and their networks "liquid communities", foregrounding the fact that their appeal doesn’t come from their amicable personality, but rather from their creative skills; and that the networks surrounding them are in a permanent flux, with members coming and going as they see fit. I argue that the "liquidness" (Bauman, 2000) of these communities is what makes them constantly creative and appealing. Textual analysis of online videos, their comments and derivatives are conducted to tease out the uses that that can be made of spoof videos, namely as phatic communication, as alternative memory and as political engagement. Through these analyses I show that spoof videos constitute not only a space where young generations can engage with each other, communicate their anger and dissatisfaction, fun and hope, and where they participate in socio-cultural and political debates, but also create a space where they can experiment with their new skills, new ideas, and new citizenship. The rise of spoof videos heralds the beginning of a trend in popular culture in contemporary China towards the "canonization of the jester" and the dethroning of the establishment. I also argue that a historical perspective is needed to understand the current surge of use creativity and user activism in China, and that many forms of popular media we experience today have their antecedents in various stages of Chinese history. The entrenched "control-resistance" binary is inadequate in interpreting the rich, flux and multilayered Internet space in China.

Summarisation of short-term and long-term videos using texture and colour

We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach. Two systems are proposed, one based solely on the BoT approach and another which exploits both colour information and BoT features. On 50 short-term videos from the Open Video Project we show that our BoT and fusion systems both achieve state-of-the-art performance, obtaining an average F-measure of 0.83 and 0.86 respectively, a relative improvement of 9% and 13% when compared to the previous state-of-the-art. When applied to a new underwater surveillance dataset containing 33 long-term videos, the proposed system reduces the amount of footage by a factor of 27, with only minor degradation in the information content. This order of magnitude reduction in video data represents significant savings in terms of time and potential labour cost when manually reviewing such footage.

Understanding and analyzing a large collection of archived swimming videos

In elite sports, nearly all performances are captured on video. Despite the massive amounts of video that has been captured in this domain over the last 10-15 years, most of it remains in an 'unstructured' or 'raw' form, meaning it can only be viewed or manually annotated/tagged with higher-level event labels which is time consuming and subjective. As such, depending on the detail or depth of annotation, the value of the collected repositories of archived data is minimal as it does not lend itself to large-scale analysis and retrieval. One such example is swimming, where each race of a swimmer is captured on a camcorder and in-addition to the split-times (i.e., the time it takes for each lap), stroke rate and stroke-lengths are manually annotated. In this paper, we propose a vision-based system which effectively 'digitizes' a large collection of archived swimming races by estimating the location of the swimmer in each frame, as well as detecting the stroke rate. As the videos are captured from moving hand-held cameras which are located at different positions and angles, we show our hierarchical-based approach to tracking the swimmer and their different parts is robust to these issues and allows us to accurately estimate the swimmer location and stroke rates.

Decolonizing digital heritage practices for Indigenous literacy: A multimodal analysis of iPad Tellagami videos

Purpose Drawing on multimodal texts produced by an Indigenous school community in Australia, we apply critical race theory and multimodal analysis to decolonize digital heritage practices for Indigenous students. This study focuses on the particular ways in which students’ counter-­‐narratives about race were embedded in multimodal and digital design in the development of a digital cultural heritage (Giaccardi, 2012). Pedagogies that explore counter-­‐narratives of cultural heritage in the official curriculum can encourage students to reframe their own racial identity, while challenging dominant white, historical narratives of colonial conquest, race, and power (Gutierrez, 2008). The children’s digital “Gami” videos, created with the iPad application, Tellagami, enabled the students to imagine hybrid, digital social identities and perspectives of Australian history that were tied to their Indigenous cultural heritage (Kamberelis, 2001).

QoE modelling for VP9 and H.265 videos on mobile devices

Current mobile devices and streaming video services support high definition (HD) video, increasing expectation for more contents. HD video streaming generally requires large bandwidth, exerting pressures on existing networks. New generation of video compression codecs, such as VP9 and H.265/HEVC, are expected to be more effective for reducing bandwidth. Existing studies to measure the impact of its compression on users’ perceived quality have not been focused on mobile devices. Here we propose new Quality of Experience (QoE) models that consider both subjective and objective assessments of mobile video quality. We introduce novel predictors, such as the correlations between video resolution and size of coding unit, and achieve a high goodness-of-fit to the collected subjective assessment data (adjusted R-square >83%). The performance analysis shows that H.265 can potentially achieve 44% to 59% bit rate saving compared to H.264/AVC, slightly better than VP9 at 33% to 53%, depending on video content and resolution.