Personalising learning through the use of technology

In March 2005, the Department for Education and Skills published its e-strategy, Harnessing Technology (DfES, 2005, Harnessing technology: Transforming Learning and Children’s Services). Within this, two of its key objectives were: firstly to transform teaching and learning, and help to improve outcomes for children and young people, through shared ideas, more exciting lessons, and online help for professionals. Secondly, to engage ‘hard to reach’ learners, with special needs support, in more motivating ways of learning, and give them more choice about how and when they learn.     

Personalising web page presentation for older people

This paper looks at different ways of personalising web page presentation to alleviate functional impairments in older people. The paper considers how impairments may be addressed by web design and through various personalisation instruments: accessibility features of standard browsers, proxy servers, assistive technology, application adaptors, and special purpose browsers. A pilot study of five older web users indicated that the most favoured personalisation technique was overriding the CSS (cascading style sheet) with a readily available one using a standard browser. The least favoured one was using assistive technology. In a follow-up study with 16 older web users, performing goal-directed browsing tasks, overriding CSS remains the most favoured. Assistive technology remains the least favoured and the slowest. Based on user comments, one-take-home message for web personalisation instrument developer is that the best instrument for older persons is one that most faithfully preserves the original layout while requiring the least effort.     

Self-calibration of stationary non-rotating zooming cameras

This paper proposes a new method for self-calibrating a set of stationary non-rotating zooming cameras. This is a realistic configuration, usually encountered in surveillance systems, in which each zooming camera is physically attached to a static structure (wall, ceiling, robot, or tripod). In particular, a linear, yet effective method to recover the affine structure of the observed scene from two or more such stationary zooming cameras is presented. The proposed method solely relies on point correspondences across images and no knowledge about the scene is required. Our method exploits the mostly translational displacement of the so-called principal plane of each zooming camera to estimate the location of the plane at infinity. The principal plane of a camera, at any given setting of its zoom, is encoded in its corresponding perspective projection matrix from which it can be easily extracted. As a displacement of the principal plane of a camera under the effect of zooming allows the identification of a pair of parallel planes, each zooming camera can be used to locate a line on the plane at infinity. Hence, two or more such zooming cameras in general positions allow the obtainment of an estimate of the plane at infinity making it possible, under the assumption of zero-skew and/or known aspect ratio, to linearly calculate the camera's parameters. Finally, the parameters of the camera and the coordinates of the plane at infinity are refined through a nonlinear least-squares optimization procedure. The results of our extensive experiments using both simulated and real data are also reported in this paper.     

Contour-based 3D motion recovery while zooming

This paper considers the problem of 3D motion recovery from a sequence of monocular images while zooming. Unlike the common trend based on point matches, the proposed method relies on the deformation of an active contour fitted to a reference object. We derive the relation between the contour deformation and the 3D motion components, assuming time-varying focal length and principal point. This relation allows us to present a method to extract the rotation matrix and the scaled translation along the optical axis.     

Image zooming via surface fitting based on edge constraint

In this paper we present a new image zooming algorithm based on surface fitting with edge constraint.In surface fitting,we consider not only the relationship of corresponding pixels between the original image and the enlarged image,but also the neighbor pixels in the enlarged image according to the local structure of original image.Furthermore,during surface fitting,more interpolation constraints are used in the new algorithm for improving the precision of the super sampling pixels.The experimental results show that the new method outperforms the previous methods which based on surface fitting.     

Distance measurement of zooming image for a mobile robot

Aiming at the application of zooming image distance measurement to mobile robot, the related key technologies are investigated in detail in this paper. Firstly, camera parameter calibration is conducted. The camera focus, optical center displacement between two foci, principal point and aberration coefficients are calculated accurately. Then, robust feature matching based on SIFT is realized by the geometrical constraint of a zooming image. Finally, the 3D reconstruction model of zooming image is established. The experimental results based on real sample images validate the practicability of the related algorithms.     

Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis

In this paper we present results of unsupervised cross-lingual speaker adaptation applied to text-to-speech synthesis. The application of our research is the personalisation of speech-to-speech translation in which we employ a HMM statistical framework for both speech recognition and synthesis. This framework provides a logical mechanism to adapt synthesised speech output to the voice of the user by way of speech recognition. In this work we present results of several different unsupervised and cross-lingual adaptation approaches as well as an end-to-end speaker adaptive speech-to-speech translation system. Our experiments show that we can successfully apply speaker adaptation in both unsupervised and cross-lingual scenarios and our proposed algorithms seem to generalise well for several language pairs. We also discuss important future directions including the need for better evaluation metrics.     

Control centric approach in designing scrolling and zooming user interfaces

The dynamic systems approach to the design of continuous interaction interfaces allows the designer to use simulations, and analytical tools to analyse the behaviour and stability of the controlled system alone and when it is coupled with a manual control model of user behaviour. This approach also helps designers to calibrate and tune the parameters of the system before the actual implementation, and in response to user feedback. In this work we provide a dynamic systems interpretation of the coupling of internal states involved in speed-dependent automatic zooming, and test our implementation on a text browser on a Pocket PC instrumented with a tilt sensor. We illustrate simulated and experimental results of the use of the proposed coupled navigation and zooming interface using tilt and touch screen input.     

Camera re-calibration after zooming based on sets of conics

We describe a method to compute the internal parameters (focal and principal point) of a camera with known position and orientation, based on the observation of two or more conics on a known plane. The conics can even be degenerate (e.g., pairs of lines). The proposed method can be used to re-estimate the internal parameters of a fully calibrated camera after zooming to a new, unknown, focal length. It also allows estimating the internal parameters when a second, fully calibrated camera observes the same conics. The parameters estimated through the proposed method are coherent with the output of more traditional procedures that require a higher number of calibration images. A deep analysis of the geometrical configurations that influence the proposed method is also reported.     

Visualizing live text streams using motion and temporal pooling

The informational context in which we live and work is becoming increasingly complex and rich, with information much more plentiful and accessible than ever before. Our informational context is also faster paced, with news and developments spreading across media and the Internet at an often astounding rate. In today's competitive world, the first response to a trend is usually the most effective. Thus far, the technology responsible for this information complexity offers little to help us quickly understand and act upon it. Although visualization is useful, its techniques are typically too slow or simply not designed to help users understand highly time-sensitive and dynamic information streams. To address this, we developed TextPool, a system that uses temporal pooling to visualize live text streams such as newswires and system telemetry. In temporal pooling, systems gather recent stream content into a buffer (pool) to use for visualization. Because the stream continues to flow through the pool in real time, the visualization must be dynamic, using motion to respond to the pool's changing content. The TextPool system processes live text streams in real time using information retrieval techniques, extracts the most frequently occurring salient terms from the buffered streams, and displays related terms next to one another in a dynamic text collage.     

In & out zooming on time-aware user/tag clusters

The common ground behind most approaches that analyze social tagging systems is addressing the information challenge that emerges from the massive activity of millions of users who interact and share resources and/or metadata online. However, lack of any time-related data in the analysis process implicitly denies much of the dynamic nature of social tagging activity. In this paper we claim that holding a temporal dimension, allows for tracking macroscopic and microscopic users’ interests, detecting emerging trends and recognizing events. To this end, we propose a time-aware co-clustering approach for acquiring semantic and temporal patterns out of the tagging activity. The resulted clusters contain both users and tags of similar patterns over time, and reveal non-obvious or “hidden” relations among users and topics of their common interest. Zoom in & out views serve as visualization methods on different aspects of the clusters’ structure, in order to evaluate the efficiency of the approach.     

Design of VCM actuator for optical zooming smartphone cameras

Microsystem Technologies - The function of optical zooming is really rare in smartphone cameras due to its appearances and dimensions now. The manufactures need to provide a better optical...     

Computing camera focal length by zooming a single point

In this paper we present a novel simple procedure to compute the focal length of a camera. The method is based on zooming in and out only a single point. The same approach allows computing the principal point when only two points are available on a pair of images surveyed with a different focal length. Experimental results show that the method is as accurate as classical full calibration methods. Moreover, its application to augmented reality produces more accurate results than those obtained when the simple pin-hole model is considered.     

高清视频监控中的图像局部放大方案

针对现代安防领域高清实时视频监控中目标点过小不易分辨的问题,为满足用户同时掌握场景全局信息与目标点处清晰的局部信息这一需求,提出了一种多屏播放系统的图像局部放大的方案.分析了软件实现的关键技术,建立了全景图像与局部图像的坐标对应关系;提出了一种鼠标定位算法并推导出相关计算公式,完成并实现了图像局部放大模块的软件代码.实验结果表明了该设计方案的准确性和有效性.     

The effects of translational misalignment when self-calibrating rotating and zooming cameras

Algorithms for self-calibrating cameras whose changes in calibration parameters are confined to rotation and zooming are useful since many real-world imaging situations do not permit translations-consider, for instance, cameras mounted on tripods and desk or wall-mounted active heads. In practice, however, the assumption of pure rotation is often violated because the optic center of the camera and the rotation center do not completely coincide. This work determines how such misalignments affect the estimation of the camera focal length. Expressions for the errors in focal length and recovered rotations are derived and results are confirmed with experiments on synthetic data. We show that the approximation of pure rotation is indeed sufficient in many cases, especially since other sources of error, such as noise and particularly radial distortion, tend to be more detrimental.     

The normalised image of the absolute conic and its application for zooming camera calibration

We present a novel technique for calibrating a zooming camera based on the invariance properties of the normalised image of the absolute conic (NIAC). We show that the camera parameters independent of position, orientation and zooming are determined uniquely by the NIAC, and we exploit these invariance properties to develop a stratified calibration method that decouples the calibration parameters. The method is organised in three steps: (i) computation of the NIAC, (ii) computation of the focal length for each image and (iii) computation of the orientation and the position of the camera. The method requires a minimum of three views of a single planar grid. Experiments with synthetic and real data suggest that the method is competitive with other state-of-the-art plane-based zooming calibration methods in the scenarios considered.     

Retrieval of real-time live fuel moisture content using MODIS measurements

Live fuel moisture content (LFMC) is one of the most important fuel properties and a critical parameter for wildland fire danger rating estimation and fire behavior analysis. Direct ground measurement of live fuel moisture content has disadvantages of high cost and limited spatial distribution extent. This paper presents an algorithm to retrieve live fuel moisture content from multiple bands of MODIS measurements. We analyzed the physical relationship between surface reflectance and live fuel moisture content using simulated MODIS measurements of diverse leaf samples, derived approximate inversion models, and proposed a semi-physical approach for live fuel moisture retrieval employing multiple MODIS bands. Using simulated MODIS measurements, the correlation coefficients between the true LFMC and estimated LFMC with our inversion models are 0.7738, 0.8397, 0.9560 and 0.9576 respectively. For validation, we tested our inversion method with woody live fuel moisture measurements at fire weather stations in Georgia. The correlation coefficients between measured LFMC and estimated LFMC with our inversion models are 0.5727, 0.6522, 0.7551, and 0.7737 respectively. Both model simulation and station measurements demonstrated advantages of our approach in accuracy. Our study suggests the potential for near real-time applications of live fuel moisture.     

Real-time ball-position measurement using multi-view cameras for live football broadcast

Multimedia Tools and Applications - We developed a robust ball-position-measurement system that can be used for actual football games. It measures the positions of a ball by integrating tracking...     

一种含参数的双线性有理插值的图像缩放方法

通过一种基于函数值的分母与分子均为一次的线性有理插值函数构造出带参数的叹线性有理插值函数,该函数形式简单,灵活度高。利用该函数提出了一种新的图像插值算法,实验表明,该方法控制灵活,能有效实现图像的缩放。     

Abstract picture generation and zooming user interface for intuitive music browsing

Today many people store music media files in personal computers or portable audio players, thanks to recent evolution of multimedia technologies. The more music media files these devices store, the messier it is to search for tunes that users want to listen to. We propose MusCat, a music browser to interactively search for the tunes according to features, not according to metadata (e.g. title, artist name). The technique firstly calculates features of tunes, and then hierarchically clusters the tunes according to the features. It then automatically generates abstract pictures, so that users can recognize characteristics of tunes more instantly and intuitionally. It finally visualizes the tunes by using abstract pictures. MusCat enables intuitive music selection with the zooming user interface.