Corpus ID: 2147556

Content-based Video Indexing and Retrieval Using Corr-LDA

@article{Iyer2016ContentbasedVI,
  title={Content-based Video Indexing and Retrieval Using Corr-LDA},
  author={Rahul Radhakrishnan Iyer and Sanjeel Parekh and Vikas Mohandoss and Anush Ramsurat and Bhiksha Raj and Rita Singh},
  journal={ArXiv},
  year={2016},
  volume={abs/1602.08581}
}
Existing video indexing and retrieval methods on popular web-based multimedia sharing websites are based on user-provided sparse tagging. This paper proposes a very specific way of searching for video clips, based on the content of the video. We present our work on Content-based Video Indexing and Retrieval using the Correspondence-Latent Dirichlet Allocation (corr-LDA) probabilistic framework. This is a model that provides for auto-annotation of videos in a database with textual descriptors… Expand
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References

SHOWING 1-10 OF 36 REFERENCES
A Survey on Visual Content-Based Video Indexing and Retrieval
TLDR
Methods for video structure analysis, including shot boundary detection, key frame extraction and scene segmentation, extraction of features including static key frame features, object features and motion features, video data mining, video annotation, and video retrieval including query interfaces are analyzed. Expand
ClassView: hierarchical video shot classification, indexing, and accessing
TLDR
This paper has proposed a novel framework, called ClassView, to make some advances toward more efficient video database indexing and access, and proposes a hierarchical semantics-sensitive video classifier to shorten the semantic gap. Expand
A probabilistic framework for semantic video indexing, filtering, and retrieval
TLDR
A probabilistic framework for semantic video indexing, which call support filtering and retrieval and facilitate efficient content-based access and demonstrates how detection performance can be significantly improved using the multinet to take interconceptual relationships into account. Expand
A Survey of Content-Based Video Retrieval
TLDR
The major themes covered by the study include shot segmentation, key frame extraction, feature extraction, clustering, indexing and video retrieval-by similarity, probabilistic, transformational, refinement and relevance feedback. Expand
Statistical motion-based video indexing and retrieval
We propose an original approach for the characterization of video dynamic content with a view to supplying new functionalities for motion-based video indexing and retrieval with query by example. WeExpand
A new approach to cross-modal multimedia retrieval
TLDR
It is shown that accounting for cross-modal correlations and semantic abstraction both improve retrieval accuracy and are shown to outperform state-of-the-art image retrieval systems on a unimodal retrieval task. Expand
Content-based image retrieval: approaches and trends of the new age
TLDR
Some of the key contributions in the current decade related to image retrieval and automated image annotation are discussed, spanning 120 references, and a study on the trends in volume and impact of publications in the field with respect to venues/journals and sub-topics is concluded. Expand
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
TLDR
The supervised formulation is shown to achieve higher accuracy than various previously published methods at a fraction of their computational cost and to be fairly robust to parameter tuning. Expand
Matching Words and Pictures
TLDR
A new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text, is presented, and a number of models for the joint distribution of image regions and words are developed, including several which explicitly learn the correspondence between regions and Words. Expand
Color histogram features based image classification in content-based image retrieval systems
  • S. Sergyán
  • Computer Science
  • 2008 6th International Symposium on Applied Machine Intelligence and Informatics
  • 2008
TLDR
A new approach is introduced, which based on low level image histogram features, the image classification is analyzed and the main advantage is the very quick generation and comparison of the applied feature vectors. Expand
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