Video browsing interfaces and applications: a review

We present a comprehensive review of the state of the art in video browsing and retrieval systems, with special emphasis on interfaces and applications. There has been a significant increase in activity (e.g., storage, retrieval, and sharing) employing video data in the past decade, both for personal and professional use. The ever-growing amount of video content available for human consumption and the inherent characteristics of video data—which, if presented in its raw format, is rather unwieldy and costly—have become driving forces for the development of more effective solutions to present video contents and allow rich user interaction. As a result, there are many contemporary research efforts toward developing better video browsing solutions, which we summarize. We review more than 40 different video browsing and retrieval interfaces and classify them into three groups: applications that use video-player-like interaction, video retrieval applications, and browsing solutions based on video surrogates. For each category, we present a summary of existing work, highlight the technical aspects of each solution, and compare them against each other

Object Segmentation in Images using EEG Signals

This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions. When an image region, specifically a block of pixels, is displayed we estimate the probability of the block containing the object of interest using a score based on EEG activity. After several such blocks are displayed, the resulting probability map is binarized and combined with the GrabCut algorithm to segment the image into object and background regions. This study shows that BCI and simple EEG analysis are useful in locating object boundaries in images.Comment: This is a preprint version prior to submission for peer-review of the paper accepted to the 22nd ACM International Conference on Multimedia (November 3-7, 2014, Orlando, Florida, USA) for the High Risk High Reward session. 10 page

Feeling what you hear: tactile feedback for navigation of audio graphs

Access to digitally stored numerical data is currently very limited for sight impaired people. Graphs and visualizations are often used to analyze relationships between numerical data, but the current methods of accessing them are highly visually mediated. Representing data using audio feedback is a common method of making data more accessible, but methods of navigating and accessing the data are often serial in nature and laborious. Tactile or haptic displays could be used to provide additional feedback to support a point-and-click type interaction for the visually impaired. A requirements capture conducted with sight impaired computer users produced a review of current accessibility technologies, and guidelines were extracted for using tactile feedback to aid navigation. The results of a qualitative evaluation with a prototype interface are also presented. Providing an absolute position input device and tactile feedback allowed the users to explore the graph using tactile and proprioceptive cues in a manner analogous to point-and-click techniques

Image grid display: A study on automatic scrolling presentation

In this paper we describe a study on image grid display with automatic vertical scrolling. While scroll operations are normally carried out manually by the user, in the context of RSVP (Rapid Serial Visual Presentation) techniques this work considers a presentation mode in which the image grid is automatically scrolled. Through experiments carried out with 50 testers, we have investigated user performance while looking for specific target subjects within large collections of images. Different numbers of columns and scrolling speeds have been considered. The search task implied both clicking on the identified target pictures and simply vocally stating their visual recognition. To this purpose, and to identify possible specific gaze behaviours, eye tracking technology has been exploited. The obtained results show that number of columns and scroll speed do affect search performance. Moreover, the userâs gaze tends to focus on different screen areas depending on the values of these two parameters. Although it is not possible to definitely find an optimal columnsâspeed combination that is valid in all cases, the particular context of use can suggest feasible solutions according to oneâs needs. To the best of our knowledge, image grid display with automatic scrolling has never been studied to date. Keywords: Image grid display, Automatic scrolling, Image presentation modes, Image collections, Rapid serial visual presentatio

Improving object segmentation by using EEG signals and rapid serial visual presentation

This paper extends our previous work on the potential of EEG-based brain computer interfaces to segment salient objects in images. The proposed system analyzes the Event Related Potentials (ERP) generated by the rapid serial visual presentation of windows on the image. The detection of the P300 signal allows estimating a saliency map of the image, which is used to seed a semi-supervised object segmentation algorithm. Thanks to the new contributions presented in this work, the average Jaccard index was improved from $0.47$ to $0.66$ when processed in our publicly available dataset of images, object masks and captured EEG signals. This work also studies alternative architectures to the original one, the impact of object occupation in each image window, and a more robust evaluation based on statistical analysis and a weighted F-score