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A multi-modal system for the retrieval of semantic video events
2004
Computer Vision and Image Understanding
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A framework for event detection is proposed where events, objects, and other semantic concepts are detected from video using trained classifiers. ...
These classifiers are used to automatically annotate video with semantic labels, which in turn are used to search for new, untrained types of events and semantic concepts. ...
Acknowledgments We are very grateful to Paul Over and Ramazan Taban, NIST, for organizing the video track. ...
doi:10.1016/j.cviu.2004.02.006
fatcat:enuxpfgaxbggphy6g2fwsgdmti
Content-based video indexing for sports applications using integrated multi-modal approach
2005
Proceedings of the 13th annual ACM international conference on Multimedia - MULTIMEDIA '05
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This doctoral consists of a research work based on an integrated multi-modal approach for sports video indexing and retrieval. ...
To sustain an ongoing rapid growth of video information, there is an emerging demand for a sophisticated content-based video indexing system. ...
This doctoral consists of a research work based on an integrated multi-modal approach for sports video indexing and retrieval. ...
doi:10.1145/1101149.1101362
dblp:conf/mm/TjondronegoroCP05
fatcat:r7flpxbh4fbfrbtnepauzo26du
Exploiting Multimedia Content: A Machine Learning Based Aproach
2014
ELCVIA Electronic Letters on Computer Vision and Image Analysis
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An experimental evaluation of the framework is shown for semantic event detection in sport videos, and semantic labelling of components of multi-modal document images. ...
The combination is also explored for semantic concept recognition using multi-modal components of the same document, and different documents over a collection. ...
An experimental evaluation of the framework is shown for semantic event detection in sport videos, and semantic labelling of components of multi-modal document images. ...
doi:10.5565/rev/elcvia.598
fatcat:mmeqgte4pzedzbtuukeepqxlgm
Semantic-Based Video Retrieval Survey
2018
Journal of Computer and Communications
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Moreover, the different methods that bridge the semantic gap in video retrieval are discussed in more details. ...
Video represents a rich source of information. Thus, there is an urgent need to retrieve, organize, and automate videos. ...
Conflicts of Interest The authors declare no conflicts of interest regarding the publication of this paper. ...
doi:10.4236/jcc.2018.68003
fatcat:qfep2py7ufhwxea7vazpujltja
Semantic Indexing of Multimedia Content Using Visual, Audio, and Text Cues
2003
EURASIP Journal on Advances in Signal Processing
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We approach the problem by developing a set of statistical models for a predefined lexicon. Novel concepts are then mapped in terms of concepts in the lexicon. ...
In this paper we present a learning-based approach to semantic indexing of multimedia content using cues derived from audio, visual and text features. ...
Figure 1 : 1 Diagram of Semantic Concept Analysis System
Figure 2 : 2 A Multi-modal Annotation Interface. ...
doi:10.1155/s1110865703211173
fatcat:rwkygctgzjfx3fey7e722djxgq
Guest editorial: web multimedia semantic inference using multi-cues
2015
World wide web (Bussum)
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A multi-modal semantic graph is constructed to find the embedded manifold cross-media correlations. The proposed method shows good performance in cross-media retrieval for image-audio dataset. ...
Multi-modality and cross-media analysis are typical ways of multi-cue analysis in Web multimedia semantic inference. ...
doi:10.1007/s11280-015-0360-2
fatcat:vc4plge5qvg7hfmza3dffmawki
A Survey of Data Representation for Multi-Modality Event Detection and Evolution
2022
Applied Sciences
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The goal of multi-modality event detection is to discover events from a huge amount of online data with different data structures, such as texts, images and videos. ...
Next, we discuss the techniques of data representation for event detection, including textual, visual, and multi-modality content. Finally, we review event evolution under multi-modality data. ...
[110] proposed a system for event extraction and retrieval called EventSearch. ...
doi:10.3390/app12042204
fatcat:5gpezz6yhjejlmdzr5fhpgka6m
Informedia @ TRECVID 2018: Ad-hoc Video Search, Video to Text Description, Activities in Extended video
2018
TREC Video Retrieval Evaluation
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In this section of the notebook, we present our system in the TRECVID Video to Text description generation task. ...
The optimization target is critical to train the encoder-decoder based video captioning models. ...
Parallel to visual semantics, learning continuous textual-visual representations have been proven useful to encode and retrieve multi-modal instances [13; 7; 3] . ...
dblp:conf/trecvid/ChenCJH00VCLHLK18
fatcat:4hie3xjj65gwdeoe7odbddrmrq
Using High-Level Semantic Features in Video Retrieval
[chapter]
2006
Lecture Notes in Computer Science
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The method can also be extended for the fusion of multi-modalities. Experiment results based on TRECVID2005 corpus demonstrate the effectiveness of the method. ...
Extraction and utilization of high-level semantic features are critical for more effective video retrieval. ...
Fig. 1 . 1 Overview of the video retrieval system
The magnitude of I(y, x i ) indicates the power of influence of event {X = x i } to event {Y = y}, while the sign of I(y, x i ) indicates the direction ...
doi:10.1007/11788034_38
fatcat:jdx7qjho6vgyze326a2upy5r6e
Fine-Grained Video-Text Retrieval With Hierarchical Graph Reasoning
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Cross-modal retrieval between videos and texts has attracted growing attentions due to the rapid emergence of videos on the web. ...
Different levels of texts can guide the learning of diverse and hierarchical video representations for cross-modal matching to capture both global and local details. ...
Conclusion Most successful cross-modal video-text retrieval systems are based on joint embedding approaches. ...
doi:10.1109/cvpr42600.2020.01065
dblp:conf/cvpr/ChenZJW20
fatcat:brlrtsp7lre7bne7cm37esr5wu
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning
[article]
2020
arXiv
pre-print
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Cross-modal retrieval between videos and texts has attracted growing attentions due to the rapid emergence of videos on the web. ...
The current dominant approach for this problem is to learn a joint embedding space to measure cross-modal similarities. ...
Conclusion Most successful cross-modal video-text retrieval systems are based on joint embedding approaches. ...
arXiv:2003.00392v1
fatcat:4yrqi2cluvhthbd5ipb4bw5zna
Semantic Based Video Retrieval System: Survey
2018
Iraqi Journal of Science
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The video retrieval system is used for finding the users' desired video among a huge number of available videos on the Internet or database. ...
This paper gives a general discussion on the overall process of the semantic video retrieval phases. ...
to obtain multi-modality and multi-concept learning leads to exploitation their respective strengths and upgrades the performance of retrieval system. ...
doi:10.24996/ijs.2018.59.2a.12
fatcat:6fvq6pygqzglbptl4czxpzbjbm
Semantics for Large-Scale Multimedia: New Challenges for NLP
2014
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: Tutorials
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Semantic Indexing
• State-of-the art frameworks
• Extension of Bag-of-Word model
• Multi-modality
3. ...
We liken "Semantic Indexing" (SIN) task, in which a system must identify occurrences of concepts such as "desk", or "dancing" in a video to the word spotting approach. ...
doi:10.3115/v1/p14-6003
dblp:conf/acl/MetzeS14
fatcat:uddxcz47sbdgbjlld5eblhvfmq
Extracting Semantics from Multimedia Content: Challenges and Solutions
[chapter]
2008
Signals and Communication Technology
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amounts of training data, and finally leveraging media semantics in retrieval systems. ...
The lack of effective indexes to describe the content of multimedia data is a main hurdle to multimedia search, and extracting semantics from multimedia content is the bottleneck for multimedia indexing ...
[42] described a joint text/image modeling approach for video retrieval that allows the full interaction between multi-modalities to result in a considerable performance improvement in TRECVID datasets ...
doi:10.1007/978-0-387-76569-3_2
fatcat:jul6fw7esfaurct6erjnvpcq6q
Unsupervised scene detection in Olympic video using multi-modal chains
2011
2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)
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This paper presents a novel unsupervised method for identifying the semantic structure in long semistructured video streams. ...
Each chain serves as an indicator that the temporal interval it demarcates is part of the same semantic event. ...
The idea is to extract features from several modalities and to unify them in a universal system of multi-modal chains, each representing a particular type of similar feature. ...
doi:10.1109/cbmi.2011.5972529
dblp:conf/cbmi/PoulisseM11
fatcat:2rbj7ejojre6hadp3ullr727gu
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