In this paper, we present an approach towards detecting semantical events from broadcasted sports video through collaborative multimedia analysis, called intermodal collaboration. Broadcasted video can be viewed as a set of multimodal streams such as visual, auditory, and textual (closed caption: CC) streams. Considering temporal dependency between their streams, we aim to improve the reliabili...

There are multiple errors in the caption for Fig 6, " Movement rates for individual Yukon River Chinook salmon returning to the Salcha and Big Salmon rivers during 2002–2004. " Please see the complete, correct Fig 6 caption here. article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided...

[1] In the paper “Scaling of small repeating earthquakes explained by interaction of seismic and aseismic slip in a rate and state fault model" by Ting Chen and Nadia Lapusta (Journal of Geophysical Research, 114, B01311, doi:10.1029/ 2008JB005749, 2009), Figure 8 had an incorrect label for the horizontal axis and hence an incorrect caption. The error does not change the conclusions of the stud...

Deaf and hearing-impaired people capture information in video through visual content and captions. Those activities require different visual attention strategies and up to now, little is known on how caption readers balance these two visual attention demands. Understanding these strategies could suggest more efficient ways of producing captions. Eye tracking and attention overload detections ar...

This article describes the participation of the Computer Science Department of Morgan State University, Baltimore, Maryland, USA in the ImageCLEFcaption under ImageCLEF 2017. The purpose of this research and participation is to be able to predict the caption and detect UMLS concepts of an unknown query (test) image by using Cross Modal Retrieval and Clustering techniques. In our approach, for e...

We study how to generate captions that are not only accurate in describing an image but also discriminative across different images. The problem is both fundamental and interesting, as most machinegenerated captions, despite phenomenal research progresses in the past several years, are expressed in a very monotonic and featureless format. While such captions are normally accurate, they often la...

In recent years there has been a growing interest in inferring social relations amongst actors in a video using audiovisual features, co-appearance features or both. The discovered relations between actors have been used for identifying leading roles, detecting rival communities in a movie plot etc. In this paper we propose an unsupervised method which uses the video’s transcript and closed cap...

Expertise in the automatic transcription of broadcast speech has progressed to the point of being able to use the resulting transcripts for information retrieval purposes. In this paper, we describe the Segmentation system used by Dragon Systems in the Segmentation task of the 1998 TDT evaluation, highlighting improvements made since the September 1998 dryrun. Segmentation of closed-caption and...

Knowledge-based numeric open caption recognition is proposed that can recognize numeric captions generated by character generator (CG) and automatically superimpose a modified caption using the recognized text only when a valid numeric caption appears in the aimed specific region of a live sportscast scene produced by other broadcasting stations. In the proposed method, mesh features are extrac...

The ever growing amount of web images and their associated texts offers new opportunities for integrative models bridging natural language processing and computer vision. However, the potential benefits of such data are yet to be fully realized due to the complexity and noise in the alignment between image content and text. We address this challenge with contributions in two folds: first, we in...