PPT-Scene text recognition in images and video

Ing Lukáš Neumann Supervisor Prof Dr Ing Ji ří Matas Problem Introduction Input Digital image BMP JPG PNG video AVI Output Set of words in the image . Wu Andrew Y Ng Computer Science Department Stanford University 353 Serra Mall Stanford CA 94305 USA acoatesblakeccbcasessanjeevbipinstwangcatdwu4ang csstanfordedu Abstract Reading text from photographs is a challenging problem that has received a si T he images can be obtained using muliple cameras or one mo ving camera T he term binocular vision is used when tw oc ameras are emplo yed brPage 2br 2 Ster eo setup and terminology Fixation point the point of intersection of the optical axis Baseli :. A Literature Survey. By:. W. Zhao, R. Chellappa, P.J. Phillips,. and A. Rosenfeld. Presented By:. Diego Velasquez. Contents . Introduction. Why do we need face recognition?. Biometrics. Face Recognition by Humans. . Quattoni. Antonio . Torralba. . CSAIL, MIT CSAIL, MIT . UC Berkeley EECS & ICSI 32 Vassar St., Cambridge, MA 02139 . ariadna@csail.mit.edu. . torralba@csail.mit.edu. . Recognizing Indoor Scenes. A general survey of previous works on. Sobhan. . Naderi. . Parizi. September 2009. List of papers. Statistical Analysis of Dynamic Actions. On Space-Time Interest Points. Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words. Badruz. . Nasrin. Bin Basri. 1051101534.  . Supervisor : . Mohd. . Haris. Lye Abdullah. 1. Contents. Introduction. 1. Literature review  . 2. Method . Used.  . 3. Experiment and Result. 4. Future works. Classification, Annotation and Segmentation in an . Automatic . Framework. Li-. Jia. Li, Richard . Socher. , Li . Fei-Fei. 1. 2. City Travel. Pagoda. Sunrise. Sunshine. Sun. 3. City Travel. Pagoda. Sunrise. Visual Persuasion in a Litigation Trial: The Case of Real Photographic Images vs. Sketched Images This study was designed to determine which kinds of graphic images were most useful as evidence in trials. Accessibility and Learning Technologies Todd M. Weissenberger IT Accessibility Coordinator, University of Iowa About this workshop Content and materials for this workshop are adapted from the forthcoming course “Inclusive Course Design: Accessibility and UDL”. Udit Roy. CVIT, IIIT Hyderabad. . Advisor: C. V. Jawahar. Co-advisor: Karteek Alahari, Inria. . . Overview. Introduction. Text Detection. Cropped Word Recognition & Retrieval. End-to-End Frameworks. Hao Zhang. Computer Science Department. 1. Problem Statement. Verification. Identification. A. B. Same / Different persons?. A. B. C. D. Which has the same identity as A?. 2. Solutions. Extensions of still face recognition algorithms. SubjectBlack in the Past TitleAda DeBlanc Simond 52 Seconds Scene 1Photo of Mrs Simond standing behind a podium with the letters NCNW National Council of Negro Women on the front panel TextAustins Bes Linda Shapiro. ECE P 596. 1. What’s Coming. Review of . Bakic. flesh . d. etector. Fleck and Forsyth flesh . d. etector. Review of Rowley face . d. etector. Overview of. . Viola Jones face detector with . Gaillynn. Clements. LiHEC. , Linguistic Society of America. Jan . 7, 2021 Virtual Conference. Presentation Focus. This presentation focuses on Cognitive and . Physical/Motor . D. isabilities. .. Visual and Auditory/Oral disabilities .