Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Contextual Priming for Object Detection
International Journal of Computer Vision
The Journal of Machine Learning Research
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Color texture measurement and segmentation
Signal Processing - Special section on content-based image and video retrieval
Creating Efficient Codebooks for Visual Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A Hierarchical Field Framework for Unified Context-Based Classification
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Putting Objects in Perspective
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Factor Graphs for Region-based Whole-scene Classification
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Robust Scene Categorization by Learning Image Statistics in Context
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
The challenge problem for automated detection of 101 semantic concepts in multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
International Journal of Computer Vision
A reranking approach for context-based concept fusion in video indexing and retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
Towards optimal bag-of-features for object categorization and semantic video retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
A Hybrid Approach to Improving Semantic Extraction of News Video
ICSC '07 Proceedings of the International Conference on Semantic Computing
Scene Classification Using a Hybrid Generative/Discriminative Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Describing Visual Scenes Using Transformed Objects and Parts
International Journal of Computer Vision
Multilevel Image Coding with Hyperfeatures
International Journal of Computer Vision
Universal and Adapted Vocabularies for Generic Visual Categorization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Episode-constrained cross-validation in video concept retrieval
IEEE Transactions on Multimedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating Color Descriptors for Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
A Learned Lexicon-Driven Paradigm for Interactive Video Retrieval
IEEE Transactions on Multimedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Validating the Detection of Everyday Concepts in Visual Lifelogs
SAMT '08 Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
Editorial: Special issue on image and video retrieval evaluation
Computer Vision and Image Understanding
Everyday concept detection in visual lifelogs: validation, relationships and trends
Multimedia Tools and Applications
Crowdsourcing rock n' roll multimedia retrieval
Proceedings of the international conference on Multimedia
Efficient targeted search using a focus and context video browser
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Bag of spatio-visual words for context inference in scene classification
Pattern Recognition
Contextual object detection using set-based classification
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
E2LSH based multiple kernel approach for object detection
Neurocomputing
Pattern Recognition Letters
Evaluating multimedia features and fusion for example-based event detection
Machine Vision and Applications
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In the face of current large-scale video libraries, the practical applicability of content-based indexing algorithms is constrained by their efficiency. This paper strives for efficient large-scale video indexing by comparing various visual-based concept categorization techniques. In visual categorization, the popular codebook model has shown excellent categorization performance. The codebook model represents continuous visual features by discrete prototypes predefined in a vocabulary. The vocabulary size has a major impact on categorization efficiency, where a more compact vocabulary is more efficient. However, smaller vocabularies typically score lower on classification performance than larger vocabularies. This paper compares four approaches to achieve a compact codebook vocabulary while retaining categorization performance. For these four methods, we investigate the trade-off between codebook compactness and categorization performance. We evaluate the methods on more than 200h of challenging video data with as many as 101 semantic concepts. The results allow us to create a taxonomy of the four methods based on their efficiency and categorization performance.