PPT-Scalable Image Annotation with

ConceptRank Petra Budíková Michal Batko Pavel Zezula Outline Searchbased annotation Motivation Problem formalization Challenges ConceptRank Idea Semantic network construction PageRank and ConceptRank. These images make up a large amount of current multimedia data and are closely related to our daily life To ef64257ciently browse retrieve and organize the web images numerous approaches have been proposed Since the semantic concepts of the images c Thesis Proposal. Tao Huang. taohuang@cs.indiana.edu. Outline. Introduction. Motivation. Related System Survey. Research Issues. Milestones. Contributions. Introduction. Annotation Definitions. A commentary on an object that: (Cousins et al. 2000). Scenes. Yu-. Shiang. Wong and Hung-. Kuo. . Chu. National Tsing Hua University. CGV LAB. Outline. Motivation. Related Works. Annotation Procedure. User Study. Motivation. Scene understanding is a popular topic.. Philip . McParlane. , Yashar Moshfeghi and Joemon M. Jose. University of Glasgow, UK. http://www.dcs.gla.ac.uk/~philip/. p.mcparlane.1@research.gla.ac.uk. Motivation for annotating images. Problems with existing automatic image annotation collections. 2. n-gram language model. 3. classifier. Studying Humour Features - Bolla, Whelan. Guidelines. define tags and describe how they should be applied. Data. 500 reviews of varying length (>7300 sentences). Thesis Proposal. Tao Huang. taohuang@cs.indiana.edu. Outline. Introduction. Motivation. Related System Survey. Research Issues. Milestones. Contributions. Introduction. Annotation Definitions. A commentary on an object that: (Cousins et al. 2000). Authors: Joe Futrelle, Amber York. . @ Woods Hole Oceanographic Institution. Imaging FlowCytobot. (Heidi Sosik et al). HabCam. (Scott . Gallager. et al). SeaBED. (. Hanumat. Singh et al). Phytoplankton . Petra Bud. íková, FI MU. CEMI meeting, Plze. ň. , 1. 6. . . 4. . 2014. Formalization. The annotation problem is . defined by a . query image . I. . and a . vocabulary . V. of candidate concepts. (ideas for . joint journal paper). CEMI meeting, Praha, 14. 3. 2014. Outline. Introduction. Why annotations?. State-of-the-art in multimedia annotation. Search-based image annotation. What. . we. . Inspirations, ideas . &. plans. Motivation. Ideal situation: general-purpose image annotation with unlimited vocabulary. Reality:. Classifiers with limited vocabulary and dependency on labeled training data. Tool. (. TART). Outline. Pragmatics & Corpora. Speech/Dialogue-Act Annotation. The DART Approach. From DART to . TART. Observations & Issues. Intended Features. Potential Applications. Pragmatics & Corpora. Omeka. Mikhail Livshits. Install. Download . the plugin at . http://omeka.org/add-ons/plugins/image-annotation. /. Upload folder to /. omeka. /plugins. Configure. Log in to . Omeka. Admin .  Manage Plugins  Configure (next to Image Annotation. Uri Avni , Tel Aviv University, Israel. Hayit. Greenspan Tel Aviv University, Israel. . Jacob Goldberger Bar . Ilan. University, Israel. Outline. Challenge description. Proposed system. Image representation. VitreoRetinal. Surgery . Vincent Ng. Xin. Yuan Wang. Background. Relevance. Project Goals. Technical Approach. Timeline. Deliverables. Assigned Responsibilities. Dependencies. Management Plan. Outline.