Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
IMOTION — A Content-based video retrieval engine
Date
2015-01-05
Author
Rossetto, Luca
Giangreco, Ivan
Schuldt, Heiko
Dupont, Stephane
Seddati, Omar
Sezgin, Metin
Sahillioğlu, Yusuf
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
175
views
0
downloads
Cite This
This paper introduces the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. For vector space retrieval, the IMOTION system exploits a large variety of low-level image and video features, as well as high-level spatial and temporal features that can all be jointly used in any combination. In addition, it supports dedicated motion features to allow for the specification of motion within a video sequence. For query specification, the IMOTION system supports query-by-sketch interactions (users provide sketches of video frames), motion queries (users specify motion across frames via partial flow fields), query-by-example (based on images) and any combination of these, and provides support for relevance feedback.
Subject Keywords
Relevance Feedback
,
Retrieval Mode
,
Query Object
,
Video Shot
,
Extraction Module
URI
https://hdl.handle.net/11511/56193
DOI
https://doi.org/10.1007/978-3-319-14442-9_24
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
IMOTION Searching for Video Sequences using Multi Shot Sketch Queries
Rossetto, Luca; Giangreco, Ivan; Heller, Silvan; Tanase, Claudiu; Schuldt, Heiko; Seddati, Omar; Dupont, Stephane; Sezgin, Tevfik Metin; Altıok, Ozan; Sahillioğlu, Yusuf (null; 2016-02-10)
This paper presents the second version of the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. Ever since, IMOTION has supported the search for video sequences on the basis of still images, user-provided sketches, or the specification of motion via flow fields. For the second version, the functionality and the usability of the system have been improved. It now supports multiple input images (such as sketches or still frames) per query, as well as the specification o...
Graph-based multilevel temporal segmentation of scripted content videos
Sakarya, Ufuk; TELATAR, ZİYA (2007-06-13)
This paper concentrates on a graph-based multilevel temporal segmentation method for scripted content videos. In each level of the segmentation, a similarity matrix of frame strings, which are series of consecutive video frames, is constructed by using temporal and spatial contents of frame strings. A strength factor is estimated for each frame string by using a priori information of a scripted content. According to the similarity matrix reevaluated from a strength function derived by the strength factors, ...
Using object-oriented materialized views to answer selection-based complex queries
Alhajj, R; Polat, Faruk (1999-09-01)
Presented in this paper is a model that utilizes existing materialized views to handle a wide range of complex selection-based queries, including linear recursive queries. Such queries are complex because it is almost impossible for naive users to predict the formulation of their predicate expressions. Object variables bound to objects in the result of a query are allowed to appear in the predicate of that query. Also, the predicate definition is extended to make it possible to have in the output only a sub...
Improving the performance of Hadoop/Hive by sharing scan and computation tasks
Özal, Serkan; Toroslu, İsmail Hakkı; Doğaç, Asuman; Department of Computer Engineering (2013)
MapReduce is a popular model of executing time-consuming analytical queries as a batch of tasks on large scale data. During simultaneous execution of multiple queries, many oppor- tunities can arise for sharing scan and/or computation tasks. Executing common tasks only once can reduce the total execution time of all queries remarkably. Therefore, we propose to use Multiple Query Optimization (MQO) techniques to improve the overall performance of Hadoop Hive, an open source SQL-based distributed warehouse sy...
WIP - SKOD: A Framework for Situational Knowledge on Demand
Palacios, Servio; Solaiman, K.M.A.; Angın, Pelin; Nesen, Alina; Bhargava, Bharat; Collins, Zachary; Sipser, Aaron; Stonebraker, Michael; Macdonald, James (2019-01-01)
Extracting relevant patterns from heterogeneous data streams poses significant computational and analytical challenges. Further, identifying such patterns and pushing analogous content to interested parties according to mission needs in real-time is a difficult problem. This paper presents the design of SKOD, a novel Situational Knowledge Query Engine that continuously builds a multi-modal relational knowledge base using SQL queries; SKOD pushes dynamic content to relevant users through triggers based on mo...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
L. Rossetto et al., “IMOTION — A Content-based video retrieval engine,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56193.