On measuring the impact of hyperlinks on reading

We increasingly spend a vast amount of time on the Web and much of that time is spent reading. One of the main differences between reading non-Web based text and reading on the Web is the presence of hyperlinks within the text, linking various related Web content and Web pages together. Some researchers and commentators have claimed that hyperlinks hinder reading because they are a distraction that may have a negative effect on the reader’s ability to process the text. However, very few controlled experiments have been conducted to verify these claims.In the experiments documented here we utilise eye tracking as a new methodology for examining how we read hyperlinked text. An eye tracker was used to observe participant’s behaviour while reading. The results showed that hyperlinked text did not generally have a negative impact upon reading behaviour. However, participants did show a tendency to re-read sentences that contained hyperlinked uncommon (low frequency) words. This suggests that hyperlinks highlight important information to the reader and the hyperlinks add additional content which for more difficult concepts, invites rereading of the preceding text

Verification of primitive Sub-Ghz RF replay attack techniques based on visual signal analysis

As the low-cost options for radio traffic capture, analysis and transmission are becoming available, some security researchers have developed open-source tools that potentially make it easier to assess the security of the devices that rely on radio communications without the need for extensive knowledge and understanding of the associated concepts. Recent research in this area suggests that primitive visual analysis techniques may be applied to decode selected radio signals successfully. This study builds upon the previous research in the area of sub-GHz radio communications and aims to outline the associated methodology as well as verify some of the reported techniques for carrying out radio frequency replay attacks using low-cost materials and freely available software

Good Features to Correlate for Visual Tracking

During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of trackers significantly affect the performance of visual tracking. The ultimate goal is to utilize robust features invariant to any kind of appearance change of the object, while predicting the object location as properly as in the case of no appearance change. As the deep learning based methods have emerged, the study of learning features for specific tasks has accelerated. For instance, discriminative visual tracking methods based on deep architectures have been studied with promising performance. Nevertheless, correlation filter based (CFB) trackers confine themselves to use the pre-trained networks which are trained for object classification problem. To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated. In order to learn the proposed model, a novel and efficient backpropagation algorithm is presented based on the loss function of the network. The proposed learning framework enables the network model to be flexible for a custom design. Moreover, it alleviates the dependency on the network trained for classification. Extensive performance analysis shows the efficacy of the proposed custom design in the CFB tracking framework. By fine-tuning the convolutional parts of a state-of-the-art network and integrating this model to a CFB tracker, which is the top performing one of VOT2016, 18% increase is achieved in terms of expected average overlap, and tracking failures are decreased by 25%, while maintaining the superiority over the state-of-the-art methods in OTB-2013 and OTB-2015 tracking datasets.Comment: Accepted version of IEEE Transactions on Image Processin

Online Object Tracking with Proposal Selection

Tracking-by-detection approaches are some of the most successful object trackers in recent years. Their success is largely determined by the detector model they learn initially and then update over time. However, under challenging conditions where an object can undergo transformations, e.g., severe rotation, these methods are found to be lacking. In this paper, we address this problem by formulating it as a proposal selection task and making two contributions. The first one is introducing novel proposals estimated from the geometric transformations undergone by the object, and building a rich candidate set for predicting the object location. The second one is devising a novel selection strategy using multiple cues, i.e., detection score and edgeness score computed from state-of-the-art object edges and motion boundaries. We extensively evaluate our approach on the visual object tracking 2014 challenge and online tracking benchmark datasets, and show the best performance.Comment: ICCV 201

Gaze-based teleprosthetic enables intuitive continuous control of complex robot arm use: Writing & drawing

Eye tracking is a powerful mean for assistive technologies for people with movement disorders, paralysis and amputees. We present a highly intuitive eye tracking-controlled robot arm operating in 3-dimensional space based on the user's gaze target point that enables tele-writing and drawing. The usability and intuitive usage was assessed by a “tele” writing experiment with 8 subjects that learned to operate the system within minutes of first time use. These subjects were naive to the system and the task and had to write three letters on a white board with a white board pen attached to the robot arm's endpoint. The instructions are to imagine they were writing text with the pen and look where the pen would be going, they had to write the letters as fast and as accurate as possible, given a letter size template. Subjects were able to perform the task with facility and accuracy, and movements of the arm did not interfere with subjects ability to control their visual attention so as to enable smooth writing. On the basis of five consecutive trials there was a significant decrease in the total time used and the total number of commands sent to move the robot arm from the first to the second trial but no further improvement thereafter, suggesting that within writing 6 letters subjects had mastered the ability to control the system. Our work demonstrates that eye tracking is a powerful means to control robot arms in closed-loop and real-time, outperforming other invasive and non-invasive approaches to Brain-Machine-Interfaces in terms of calibration time (<;2 minutes), training time (<;10 minutes), interface technology costs. We suggests that gaze-based decoding of action intention may well become one of the most efficient ways to interface with robotic actuators - i.e. Brain-Robot-Interfaces - and become useful beyond paralysed and amputee users also for the general teleoperation of robotic and exoskeleton in human augmentation

Skim reading: an adaptive strategy for reading on the web

It has been suggested that readers spend a great deal of time skim reading on the Web and that if readers skim read they reduce their comprehension of what they have read. There have been a number of studies exploring skim reading, but relatively little exists on the skim reading of hypertext and Webpages. In the experiment documented here, we utilised eye tracking methodology to explore how readers skim read hypertext and how hyperlinks affect reading behaviour. The results show that the readers read faster when they were skim reading and comprehension was reduced. However, the presence of hyperlinks seemed to assist the readers in picking out important information when skim reading. We suggest that readers engage in an adaptive information foraging strategy where they attempt to minimise comprehension loss while maintaining a high reading speed. Readers use hyperlinks as markers to suggest important information and use them to read through the text in an efficient and effective way. This suggests that skim reading may not be as damaging to comprehension when reading hypertext, but it does mean that the words we choose to hyperlink become very important to comprehension for those skim reading text on the Web