Deep Multimodal Speaker Naming

Automatic speaker naming is the problem of localizing as well as identifying each speaking character in a TV/movie/live show video. This is a challenging problem mainly attributes to its multimodal nature, namely face cue alone is insufficient to achieve good performance. Previous multimodal approaches to this problem usually process the data of different modalities individually and merge them using handcrafted heuristics. Such approaches work well for simple scenes, but fail to achieve high performance for speakers with large appearance variations. In this paper, we propose a novel convolutional neural networks (CNN) based learning framework to automatically learn the fusion function of both face and audio cues. We show that without using face tracking, facial landmark localization or subtitle/transcript, our system with robust multimodal feature extraction is able to achieve state-of-the-art speaker naming performance evaluated on two diverse TV series. The dataset and implementation of our algorithm are publicly available online

The Cowl - v.67 - n.15 - Feb 6, 2003

The Cowl - student newspaper of Providence College. Vol 67 - No. 15 - February 6, 2003. 28 pages

The Daily Texan

Texas Student Medi

An Effective Technique for Removal of Facial Dupilcation by SBFA

Search based face annotation (SBFA) is an effective technique to annotate the weakly labeled facial images that are freely available on World Wide Web. The main objective of search based face annotation is to assign correct name labels to given query facial image. One difficult drawback for search based face annotation theme is how to effectively perform annotation by exploiting the list of most similar facial pictures and their weak labels that square measure typically droning and incomplete. To tackle this drawback, we tend to propose a good unattended label refinement (URL) approach for purification the labels of web facial pictures exploitation machine learning technique. We tend to formulate the educational drawback as a gibbose improvement and develop effective improvement algorithms to resolve the large scale learning task expeditiously. To additional speed up the projected theme, we also proposed clustering based approximation algorithmic program which may improve quantify ability significantly. We have conducted an in depth set of empirical studies on a large scale net facial image test bed, within which encouraging results showed that the projected URL algorithms will considerably boost the performance of the promising SBFA theme. In future work we will use HAAR algorithm. HAAR is feature based method for face detection. HAAR features, integral images, recognized detection of features improve face detection in terms of speed and accuracy. DOI: 10.17762/ijritcc2321-8169.150517

Informedia at TRECVID 2003: Analyzing and searching broadcast news video

We submitted a number of semantic classifiers, most of which were merely trained on keyframes. We also experimented with runs of classifiers were trained exclusively on text data and relative time within the video, while a few were trained using all available multiple modalities. 1.2 Interactive search This year, we submitted two runs using different versions of the Informedia systems. In one run, a version identical to last year's interactive system was used by five researchers, who split up the topics between themselves. The system interface emphasizes text queries, allowing search across ASR, closed captions and OCR text. The result set can then be manipulated through: • storyboards of images spanning across video story segments • emphasizing matching shots to a user’s query to reduce the image count to a manageable size • resolution and layout under user control • additional filtering provided through shot classifiers such as outdoors, and shots with people, etc. • display of filter count and distribution to guide their use in manipulating storyboard views. In the best-performing interactive run, for all topics a single researcher used an improved version of the system, which allowed more effective browsing and visualization of the results of text queries using

The films of Chantal Akerman : a cinema of displacements

This thesis attempts to broaden the critical boundaries within which the films of Chantal Akerman have been discussed. First, it extends analysis from Akerman's 70s to her 80s and 90s films. Second, it argues that as well as her gender and aesthetic identities, Akerman's Belgian and Jewish identities should be acknowledged. Finally, it suggests that each of these four identities: woman, independent film-maker, Belgian and Jewish allow her a position of marginality, figured in her films through the trope of 'displacement'. The structure of the thesis is two-fold: it extends discussion of Akerman's cinema to films not previously considered, and through this extension engages with contemporary issues in film and cultural theory such as female authorship, independent and national, and marginal cinemas. Chapter one `Woman' and chapter two `Independent' extend the reading of gender and sexuality and formal and aesthetic innovation in Akerman's cinema. In the first chapter this is done through consideration of the films Golden Eighties (1986) and Nuit et jour (1990), while in the second her short films, video work and work for television are examined. My third and fourth chapters offer areas of Akerman's work which have not previously been studied. Chapter three, `Belgian', considers the significance of Akerman's nationality for her film-making while engaging with theories around national cinema. It examines the possibility of a `Belgian national cinema' and the intersections which arise between this and Akerman's cinema, especially around Toute une nuit (1982). Finally, in my fourth chapter, `Jewish', I use Histoires d'Amerigue (1989) and D'Est (1993) to argue that Akerman's is a `wandering' cinema, in which she is constantly examining the homelessness and displacement that her Jewishness engenders

Spartan Daily, September 8, 2016

Volume 147, Issue 5https://scholarworks.sjsu.edu/spartan_daily_2016/1045/thumbnail.jp

Xavier University Newswire

https://www.exhibit.xavier.edu/student_newspaper/1675/thumbnail.jp