Doing Qualitative Research

http://clintlalonde.net/wp-content/uploads/2012/09/instructionalvideo.pdf

Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness

VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method

https://bura.brunel.ac.uk/bitstream/2438/8012/2/Fulltext.pdf

Video summarisation: A conceptual framework and survey of the state of the art

In this paper, we review 300 references on video retrieval, indicating when text-only solutions are unsatisfactory and showing the promising alternatives which are in majority concept-based. Therefore, central to our discussion is the notion of a semantic concept: an objective linguistic description of an observable entity. Specifically, we present our view on how its automated detection, selection under uncertainty, and interactive usage might solve the major scientific problem for video retrieval: the semantic gap. To bridge the gap, we lay down the anatomy of a concept-based video search engine. We present a component-wise decomposition of such an interdisciplinary multimedia system, covering influences from information retrieval, computer vision, machine learning, and human–computer interaction. For each of the components we review state-of-the-art solutions in the literature, each having different characteristics and merits. Because of these differences, we cannot understand the progress in video retrieval without serious evaluation efforts such as carried out in the NIST TRECVID benchmark. We discuss its data, tasks, results, and the many derived community initiatives in creating annotations and baselines for repeatable experiments. We conclude with our perspective on future challenges and opportunities.

/pdf/concept-based-video-retrieval-1iy430iazc.pdf

Concept-Based Video Retrieval

Affect and emotion play an important role in our everyday lives: They are present whatever we do, wherever we are, and wherever we go, without us being aware of them for much of the time. When it comes to interaction, be it with humans, technology, or humans via technology, we suddenly become more aware of emotion, either by seeing the others emotional expression, or by not getting an emotional response while anticipating one. Given this, it seems only sensible to explore affect and emotion in human-computer interaction, to investigate the underlying principles, to study the role they play, to develop methods to quantify them, and to finally build applications that make use of them. This is the research field for which, over ten years ago, Rosalind Picard coined the phrase "affective computing". The present book provides an account of the latest work on a variety of aspects related to affect and emotion in human-technology interaction. It covers theoretical issues, user experience and design aspects as well as sensing issues, and reports on a number of affective applications that have been developed in recent years.

Affect and Emotion in Human-Computer Interaction

https://bura.brunel.ac.uk/bitstream/2438/8790/3/Fulltext.pdf

Analysing user physiological responses for affective video summarisation

MPEG-7: Multimedia Content Description Interface.

Video summaries present the user with a condensed and succinct representation of the content of a video stream. Usually this is achieved by attaching degrees of importance to low-level image, audio and text features. However, video content elicits strong and measurable physiological responses in the user, which are potentially rich indicators of what video content is memorable to or emotionally engaging for an individual user. This article proposes a technique that exploits such physiological responses to a given video stream by a given user to produce Entertainment-Led VIdeo Summaries (ELVIS). ELVIS is made up of five analysis phases which correspond to the analyses of five physiological response measures: electro-dermal response (EDR), heart rate (HR), blood volume pulse (BVP), respiration rate (RR), and respiration amplitude (RA). Through these analyses, the temporal locations of the most entertaining video subsegments, as they occur within the video stream as a whole, are automatically identified. The effectiveness of the ELVIS technique is verified through a statistical analysis of data collected during a set of user trials. Our results show that ELVIS is more consistent than RANDOM, EDR, HR, BVP, RR and RA selections in identifying the most entertaining video subsegments for content in the comedy, horror/comedy, and horror genres. Subjective user reports also reveal that ELVIS video summaries are comparatively easy to understand, enjoyable, and informative.

/pdf/elvis-entertainment-led-video-summaries-40j12orcbc.pdf

Harry Agius

Papers

Video summarisation: A conceptual framework and survey of the state of the art

Affect and Emotion in Human-Computer Interaction

Analysing user physiological responses for affective video summarisation

MPEG-7: Multimedia Content Description Interface.

ELVIS: Entertainment-led video summaries