Non-goal scene analysis for soccer video

The broadcast soccer video is usually recorded by one main camera, which is constantly gazing somewhere of playfield where a highlight event is happening. So the camera parameters and their variety have close relationship with semantic information of soccer video, and much interest has been caught in camera calibration for soccer video. The previous calibration methods either deal with goal scene, or have strict calibration conditions and high complexity. So, it does not properly handle the non-goal scene such as midfield or center-forward scene. In this paper, based on a new soccer field model, a field symbol extraction algorithm is proposed to extract the calibration information. Then a two-stage calibration approach is developed which can calibrate camera not only for goal scene but also for non-goal scene. The preliminary experimental results demonstrate its robustness and accuracy. (c) 2010 Elsevier B.V. All rights reserved.

A Video Quality Assessment Metric Based on Human Visual System

It is important for practical application to design an effective and efficient metric for video quality. The most reliable way is by subjective evaluation. Thus, to design an objective metric by simulating human visual system (HVS) is quite reasonable and available. In this paper, the video quality assessment metric based on visual perception is proposed. Three-dimensional wavelet is utilized to decompose video and then extract features to mimic the multichannel structure of HVS. Spatio-temporal contrast sensitivity function (S-T CSF) is employed to weight coefficient obtained by three-dimensional wavelet to simulate nonlinearity feature of the human eyes. Perceptual threshold is exploited to obtain visual sensitive coefficients after S-T CSF filtered. Visual sensitive coefficients are normalized representation and then visual sensitive errors are calculated between reference and distorted video. Finally, temporal perceptual mechanism is applied to count values of video quality for reducing computational cost. Experimental results prove the proposed method outperforms the most existing methods and is comparable to LHS and PVQM.

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.

Towards an Example-Based Image Compression Architecture for Video-Conferencing

This paper consists of two major parts. First, we present the outline of a simple approach to very-low bandwidth video-conferencing system relying on an example-based hierarchical image compression scheme. In particular, we discuss the use of example images as a model, the number of required examples, faces as a class of semi-rigid objects, a hierarchical model based on decomposition into different time-scales, and the decomposition of face images into patches of interest. In the second part, we present several algorithms for image processing and animation as well as experimental evaluations. Among the original contributions of this paper is an automatic algorithm for pose estimation and normalization. We also review and compare different algorithms for finding the nearest neighbors in a database for a new input as well as a generalized algorithm for blending patches of interest in order to synthesize new images. Finally, we outline the possible integration of several algorithms to illustrate a simple model-based video-conference system.

Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame

Passive monitoring of large sites typically requires coordination between multiple cameras, which in turn requires methods for automatically relating events between distributed cameras. This paper tackles the problem of self-calibration of multiple cameras which are very far apart, using feature correspondences to determine the camera geometry. The key problem is finding such correspondences. Since the camera geometry and photometric characteristics vary considerably between images, one cannot use brightness and/or proximity constraints. Instead we apply planar geometric constraints to moving objects in the scene in order to align the scene"s ground plane across multiple views. We do not assume synchronized cameras, and we show that enforcing geometric constraints enables us to align the tracking data in time. Once we have recovered the homography which aligns the planar structure in the scene, we can compute from the homography matrix the 3D position of the plane and the relative camera positions. This in turn enables us to recover a homography matrix which maps the images to an overhead view. We demonstrate this technique in two settings: a controlled lab setting where we test the effects of errors in internal camera calibration, and an uncontrolled, outdoor setting in which the full procedure is applied to external camera calibration and ground plane recovery. In spite of noise in the internal camera parameters and image data, the system successfully recovers both planar structure and relative camera positions in both settings.

Learning object segmentation from video data

This memo describes the initial results of a project to create a self-supervised algorithm for learning object segmentation from video data. Developmental psychology and computational experience have demonstrated that the motion segmentation of objects is a simpler, more primitive process than the detection of object boundaries by static image cues. Therefore, motion information provides a plausible supervision signal for learning the static boundary detection task and for evaluating performance on a test set. A video camera and previously developed background subtraction algorithms can automatically produce a large database of motion-segmented images for minimal cost. The purpose of this work is to use the information in such a database to learn how to detect the object boundaries in novel images using static information, such as color, texture, and shape. This work was funded in part by the Office of Naval Research contract #N00014-00-1-0298, in part by the Singapore-MIT Alliance agreement of 11/6/98, and in part by a National Science Foundation Graduate Student Fellowship.

Foundations of Actor Semantics

The actor message-passing model of concurrent computation has inspired new ideas in the areas of knowledge-based systems, programming languages and their semantics, and computer systems architecture. The model itself grew out of computer languages such as Planner, Smalltalk, and Simula, and out of the use of continuations to interpret imperative constructs within A-calculus. The mathematical content of the model has been developed by Carl Hewitt, Irene Greif, Henry Baker, and Giuseppe Attardi. This thesis extends and unifies their work through the following observations. The ordering laws postulated by Hewitt and Baker can be proved using a notion of global time. The most general ordering laws are in fact equivalent to an axiom of realizability in global time. Independence results suggest that some notion of global time is essential to any model of concurrent computation. Since nondeterministic concurrency is more fundamental than deterministic sequential computation, there may be no need to take fixed points in the underlying domain of a power domain. Power domains built from incomplete domains can solve the problem of providing a fixed point semantics for a class of nondeterministic programming languages in which a fair merge can be written. The event diagrams of Greif's behavioral semantics, augmented by Baker's pending events, form an incomplete domain. Its power domain is the semantic domain in which programs written in actor-based languages are assigned meanings. This denotational semantics is compatible with behavioral semantics. The locality laws postulated by Hewitt and Baker may be proved for the semantics of an actor-based language. Altering the semantics slightly can falsify the locality laws. The locality laws thus constrain what counts as an actor semantics.

Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough-Based Approaches

R. Jensen and Q. Shen. Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough Based Approaches. IEEE Transactions on Knowledge and Data Engineering, 16(12): 1457-1471. 2004.

Trash or Treasure? Censorship and the Changing Meanings of the Video Nasties

Egan, K. (2007). Trash or Treasure?: Censorship and the Changing Meanings of the Video Nasties. InsidePopular Film. Manchester: Manchester University Press. RAE2008

BitBox!: A case study interface for teaching real-time adaptive music composition for video games

Real-time adaptive music is now well-established as a popular medium, largely through its use in video game soundtracks. Commercial packages, such as fmod, make freely available the underlying technical methods for use in educational contexts, making adaptive music technologies accessible to students. Writing adaptive music, however, presents a significant learning challenge, not least because it requires a different mode of thought, and tutor and learner may have few mutual points of connection in discovering and understanding the musical drivers, relationships and structures in these works. This article discusses the creation of ‘BitBox!’, a gestural music interface designed to deconstruct and explain the component elements of adaptive composition through interactive play. The interface was displayed at the Dare Protoplay games exposition in Dundee in August 2014. The initial proof-of- concept study proved successful, suggesting possible refinements in design and a broader range of applications.

Aspects of Semantics and Pragmatics of Dialogue. SemDial 2010, 14th Workshop on the Semantics and Pragmatics of Dialogue

The papers collected in this book cover a range of topics in semantics and pragmatics of dialogue. All these papers were presented at SemDial 2010, the 14th Workshop on the Semantics and Pragmatics of Dialogue. This 14th edition in the SemDial series, also known as PozDial, took place in Poznań (Poland) in June 2010, and was organized by the Chair of Logic and Cognitive Science (Institute of Psychology, Adam Mickiewicz University). From over 30 submissions overall, 14 were accepted as full papers for plenary presentation at the workshop, and all are included in this book. In addition, 10 were accepted as posters, and are included here as 2-4 page short papers. Finally, we also include abstracts from our keynote speakers. We hope that the ideas gathered in this book will be a valuable source of up-to-date achievements in the field, and will become a valuable inspiration for new ones. We would like to express our thanks to all those who submitted to and participated in SemDial 2010, especially the invited speakers: Dale Barr (University of Glasgow), Jonathan Ginzburg (King's College London), Jeroen Groenendijk (University of Amsterdam) and Henry Prakken (Utrecht University, The University of Groningen). Last but not least, we would like to thank everybody engaged in the workshop organization -- the chairs, the local organizing committee for their hard work in Poznań, and the programme committee members for their thorough and helpful reviews.

Teaching Competences and their Development Via Video-Recording

The article deals with use of case studies for professional preparation of teachers to be. One of the suitable ways to develop professional teaching competences is to apply the method of a case study. A case study means a complex and creative solution for a given teaching situation in simulated teaching conditions. It is based on interactive and situational education and decision taking. A case study improves not only professional and teaching competences for becoming teachers – it also fulfi ls the task to develop at students their auto-evaluating and auto-refl exing skills. To increase professional competences it is mandatory to do a complex analysis of the video-record for the implemented study. A complex analysis is a subject of the research project of a student grant agency at the University of West Bohemia in Pilsen.