PPT-Image and Video Retrieval

INST 734 Doug Oard Module 13 Agenda Image retrieval Video retrieval Multimedia retrieval Multimedia A set of timesynchronized modalities Video Images object motion camera motion scenes. CSC 575. Intelligent Information Retrieval. Intelligent Information Retrieval. 2. Retrieval Models. Model is an idealization or abstraction of an actual process. in this case, process is matching of documents with queries, i.e., retrieval. Pattern Completion and Recapitulation. Episodic Retrieval and the Frontal Lobes. Cues for Retrieval. The Second Time Around: Recognizing Stimuli by Recollection and Familiarity. Misremembering the Past. INST 734. Module 3. Doug . Oard. Agenda. Ranked retrieval. Similarity-based ranking. Probability-based ranking. Boolean Retrieval. Strong points. Accurate, . if you know the right strategies. Efficient for the computer. CSC . 575. Intelligent Information Retrieval. 2. Source: . Intel. How much information?. Google: . ~100 . PB a . day; 3+ million servers (15 . Exabytes. stored). Wayback Machine has . ~9 . PB + . 100 . Petr Doubek, Jiri Matas, Michal Perdoch and Ondrej Chum. Center. for Machine Perception, Czech Technical University in Prague, Czech Republic. Detection of repetitive patterns in images is a well-established computer vision problem. However, the detected patterns are rarely used in any application. A method for representing a lattice or line pattern by shift-invariant descriptor of the repeating tile is presented. The descriptor respects the inherent shift ambiguity of the tile definition and is robust to viewpoint change. Repetitive structure matching is demonstrated in a retrieval experiment where images of buildings are retrieved solely by repetitive patterns.. circulant. temporal encoding. CVPR 2013 . Oral. Outline. 1. . Introduction. 2. EVVE: an event retrieval . dataset. 3. Frame . description. 4. . Circulant. temporal . aggregation. 5. Indexing strategy and . Information. Miles Efron, Jana . Diesner. , Peter . Organisciak. , Garrick Sherman, Ana . Lucic. {. mefron. , et al.}@. illinois.edu. GSLIS 2012. TREC: The Text REtrieval Conference. NIST. Web. Legal. Group 3. Chad Mills. Esad Suskic. Wee Teck Tan. Outline. System and Data. Document Retrieval. Passage Retrieval. Results. Conclusion. System and Data. Development. Testing. TREC 2004. TREC 2004. TREC 2005. and Re-ranking. Ling573. NLP Systems and Applications. May 3, 2011. Upcoming Talks. Edith Law. Friday: 3:30; CSE 303. Human Computation: Core Research Questions and Opportunities . Games with a purpose, . Hongning. Wang. CS@UVa. What is information retrieval?. CS6501: Information Retrieval. CS@UVa. 2. Why information retrieval . Information overload. “. It refers to the . difficulty. a person can have understanding an issue and making decisions that can be caused by the presence of . BY. DR. ADNAN ABID. Lecture # . Introduction. Library Management System. Structured Data Storage / Tables. Semi-Structured and Unstructured . Employee Department Salary. Library Digitization. Information Retrieval Models. Fatemeh. Azimzadeh. Books. (Manning et al., 2008). Christopher D. Manning, . Prabhakar. . Raghavan. , and . Hinrich. . Schütze. . Introduction to Information Retrieval. Cambridge University Press, 2008. . Retrieval Practice: Lesson 3. 1. What is an . autobiography. ?.  .  2. Does Roald Dahl consider . Boy . to be an . autobiography. ? Why or why not?.  .  3. What is an . anecdote. ?.  . 4. Describe one . Dr. S. . Parthasarathy. . MD., DA., DNB, MD (. Acu. ), Dip. . Diab. . DCA, Dip. Software statistics- . PhD ( physiology), IDRA . IVF techniques include:. a. . Ovarian stimulation and monitoring.. b. Ultrasound-directed .