Using decision-tree to automatically construct learned-heuristics for events classification in sports video

Automatic events classification is an essential requirement for constructing an effective sports video summary. It has become a well-known theory that the high-level semantics in sport video can be “computationally interpreted” based on the occurrences of specific audio and visual features which can be extracted automatically. State-of-the-art solutions for features-based event classification have only relied on either manual-knowledge based heuristics or machine learning. To bridge the gaps, we have successfully combined the two approaches by using learning-based heuristics. The heuristics are constructed automatically using decision tree while manual supervision is only required to check the features and highlight contained in each training segment. Thus, fully automated construction of classification system for sports video events has been achieved. A comprehensive experiment on 10 hours video dataset, with five full-match soccer and five full-match basketball videos, has demonstrated the effectiveness/robustness of our algorithms.

Coastal marine habitat mapping using multi-beam acoustics, video data and a decision tree classifier on the temperate south-east Australian continental shelf

In this habitat mapping study, multi-beam acoustic data are integrated with extensive, precisely geo-referenced video validation data in a GIS environment to classify benthic substrates and biota at a 33km2 site in the near shore waters of Victoria, Australia. Using an automated decision-tree classification method, 5 representative biotic groups were identified in the Cape Nelson survey area using a combination of multi-beam bathymetry, backscatter and derivative products. Rigorous error assessment of derived, classified maps produced high overall accuracies (>85%) for all mapping products. In addition, a discrete multivariate analysis technique (kappa analysis) was used to assess classification accuracy. High-resolution (2.5m cell-size) representation of sea floor morphology and textural characteristics provided by multi-beam bathymetry and backscatter datasets, allowed the interpretation of benthic substrates of the Cape Nelson site and the communities of sessile organisms that populate them. Non-parametric multivariate statistical analysis (ANOSIM) revealed a significant difference in biotic composition between depth strata, and between substrate types. Incorporated with other descriptive measures, these results indicate that depth and substrate are important factors in the distributional ecology of the biotic communities at the Cape Nelson study site. BIOENV analysis indicates that derivatives of both multi-beam datasets (bathymetry and backscatter) are correlated with distribution and density of biotic communities. Results from this study provide new tools for research and management of the coastal zone.

History, memory, and the politics of programming : the video work of Richard Fung

Richard Fung, a Toronto-based video artist and cultural critic, was born in Trinidad in 1954, and attended school in Ireland before immigrating to Canada to study at the University of Toronto. Richard Fung has taught at the Ontario College of Art and Design, and has been a visiting professor in the Department of Media Study at the State University of New York in Buffalo. He is currently the coordinator of the Centre for Media and Culture in Education, Ontario Institute for Studies in Education, University of Toronto.

Documentary display : re-viewing nonfiction film and video

Not all documentary films and videos are sober depictions of the real world. Documentary representations can present expressive, entertaining and spectacular images. This book examines such innovative approaches as they occur within the process of 'documentary display' - a practice which emphasises the visual attractions of documentary representation. Works of documentary display explore modes of exhibitionistic 'showing' in which sensation is frequently the vehicle of cognition and knowledge. Such a display is analysed within the popular and prominent forms of found-footage film, 'rockumentary', the city film, nonfiction surf film and video, and certain views of natural science topics. This accessible and informed study - with its focus on entertaining, popular, spectacular and sensational froms of nonfiction representation - makes an important contribution to theoretical analyses of documentary film and video

A scalable and extensible segment-event-object-based sports video retrieval system

Sport video data is growing rapidly as a result of the maturing digital technologies that support digital video capture, faster data processing, and large storage. However, (1) semi-automatic content extraction and annotation, (2) scalable indexing model, and (3) effective retrieval and browsing, still pose the most challenging problems for maximizing the usage of large video databases. This article will present the findings from a comprehensive work that proposes a scalable and extensible sports video retrieval system with two major contributions in the area of sports video indexing and retrieval. The first contribution is a new sports video indexing model that utilizes semi-schema-based indexing scheme on top of an Object-Relationship approach. This indexing model is scalable and extensible as it enables gradual index construction which is supported by ongoing development of future content extraction algorithms. The second contribution is a set of novel queries which are based on XQuery to generate dynamic and user-oriented summaries and event structures. The proposed sports video retrieval system has been fully implemented and populated with soccer, tennis, swimming, and diving video. The system has been evaluated against 20 users to demonstrate and confirm its feasibility and benefits. The experimental sports genres were specifically selected to represent the four main categories of sports domain: period-, set-point-, time (race)-, and performance-based sports. Thus, the proposed system should be generic and robust for all types of sports.

Adaptive fusion of gait and face for human identification in video

Most work on multi-biometric fusion is based on static fusion rules which cannot respond to the changes of the environment and the individual users. This paper proposes adaptive multi-biometric fusion, which dynamically adjusts the fusion rules to suit the real-time external conditions. As a typical example, the adaptive fusion of gait and face in video is studied. Two factors that may affect the relationship between gait and face in the fusion are considered, i.e., the view angle and the subject-to-camera distance. Together they determine the way gait and face are fused at an arbitrary time. Experimental results show that the adaptive fusion performs significantly better than not only single biometric traits, but also those widely adopted static fusion rules including SUM, PRODUCT, MIN, and MAX.

Teaching and learning force as a representational issue : insights from a classroom video study

An enormous amount of research in the conceptual change tradition has shown the difficulty of learning fundamental science concepts, yet conceptual change schemes have failed to convincingly demonstrate improvements in supporting significant student learning. Recent work in cognitive science has challenged this purely conceptual view of learning, emphasising the role of languages, and the importance of personal and contextual aspects of  understanding science. The research described in this paper is designed around the notion that learning involves the recognition and development of students’ representational resources. In particular, we argue that difficulties with the concept of force are fundamentally representational in nature. The paper describes the planning and implementation of a classroom sequence in force that focuses on representations and their negotiation, and reports on the effectiveness of this perspective in guiding teaching and learning. Classroom sequences involving three teachers 158 2008 NARST Annual International Conference were videotaped using a combined focus on the teacher and groups of students. Video analysis software was used to code the variety of representations used, and sequences of representational negotiation. Stimulated recall interviews were conducted with teachers and students. The paper will report on the effect of this approach on teacher knowledge and pedagogy, and on student learning of force.

Testimony and memory : re-writeable video memoirs

In Chris Marker’s Sunless (1985), the narrator states: “We do not remember, we re-write memory much as history is rewritten.” This presentation considers the ways in which my parents’ stories have been (and can be) re-written. In 1996, my father and mother engaged in a process of remembering, narrating and re-considering their histories when their video testimonies were recorded for the Survivors of the Shoah Visual History Foundation. They experienced much of World War II in different locations – only re-united after many months. For these video testimonies, they were recorded separately – once again, with a distance of many months between. Whenever there is an attempt to protect a story from interruption and contradiction, narrative multiplicity arises. By comparing and analysing their separate stories in terms of what was said, what was not said, what was unspeakable, and what was unknowable, I am interested in the uncertainties, the gaps, and the different ways in which they attempted to re-make their own histories whilst in the midst of storytelling. I am also interested in re-editing these memoirs into a multi-perspectival family video album, in which the stories and storytellers re-inhabit a shared and re-writeable space of storytelling.