The INRIA-LIM-VocR and AXES submissions to TrecVid 2014 Multimedia Event Detection
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Summary
This paper describes the participation of INRIA-LIM-VocR and AXES to the 2014 edition of the TrecVid Multimedia Event Detection task, and presents an overview of the features and the classification techniques.
- Type
- preprint
- Published
- 2014-01-01
- Cited by
- 9
- References
- 29
- Access
- Open access
- OpenAlex
- https://openalex.org/W934447755
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9203757
Keywords
Computer science, Event (particle physics), Pattern recognition (psychology), Object (grammar), Artificial intelligence
References
- Partitioning and transcription of broadcast news data
- Using MLP features in SRI's conversational speech recognition system
- The Kaldi Speech Recognition Toolkit
- The AXES submissions at TRECVID 2013
- Image Classification with the Fisher Vector: Theory and Practice
- The LIMSI Broadcast News transcription system
- Modeling spatial layout with fisher vectors for image categorization
- Rapid development of a Latvian speech-to-text system
- Perceptual linear predictive (PLP) analysis of speech.
- Label-Embedding for Attribute-Based Classification
- ImageNet Large Scale Visual Recognition Challenge
- Robust wide-baseline stereo from maximally stable extremal regions
- HMDB: A large video database for human motion recognition
- Action and Event Recognition with Fisher Vectors on a Compact Feature Set
- Distinctive Image Features from Scale-Invariant Keypoints
- LIBSVM: A library for support vector machines
- Caffe: Convolutional Architecture for Fast Feature Embedding
- Multiscale Scattering for Audio Classification
- Towards Lower Error Rates in Phoneme Recognition
- AXES at TRECVID 2012: KIS, INS, and MED
Cited by
- Supervised Learning Approaches for Automatic Structuring of Videos. (Méthodes d'apprentissage supervisé pour la structuration automatique de vidéos)
- Learning to detect video events from zero or very few video examples
- Humans in Action at Different Levels: the group, the whole, and the parts
- Machine learning solutions to visual recognition problems
- Maximum margin learning under uncertainty
- Education and Employment Main Activities
- Video Event Detection Using Kernel Support Vector Machine with Isotropic Gaussian Sample Uncertainty (KSVM-iGSU)
- ForgetIT Concise Preservation by Combining Managed Forgetting and Contextualized Remembering
- Activity Report 2014 Project-Team LEAR Learning and recognition in vision
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