Joint segmentation and classification of human actions in video
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- Type
- article
- Published
- 2011-06-20
- Cited by
- 278
- References
- 27
- OpenAlex
- https://openalex.org/W1978511849
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:340162
Keywords
Computer science, Artificial intelligence, Segmentation, Discriminative model, Pattern recognition (psychology)
References
- Actions as space-time shapes
- Learning and Inferring Motion Patterns using Parametric Segmental Switching Linear Dynamic Systems
- Action unit detection with segment-based SVMs
- Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
- Leveraging temporal, contextual and ordering constraints for recognizing complex activities in video
- Weakly supervised discriminative localization and classification: a joint learning process
- Kernel Change-point Analysis
- Discovery and Segmentation of Activities in Video
- Visual quasi-periodicity
- Event Detection in Crowded Videos
- Hidden Markov Support Vector Machines
- Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
- Learning realistic human actions from movies
- Statistical analysis of dynamic actions
- Modeling changing dependency structure in multivariate time series
- Robust Real-Time Periodic Motion Detection, Analysis, and Applications
- Conditional models for contextual human motion recognition
- Machine Recognition of Human Activities: A Survey
- On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines
- Discriminative human action segmentation and recognition using semi-Markov model
Cited by
- Modèles structurés pour la reconnaissance d'actions dans des vidéos réalistes
- Graphical Models for Wide-Area Activity Analysis in Continuous Videos
- 3D Robotic Sensing of People: Human Perception, Representation and Activity Recognition
- Segment-based SVMs for Time Series Analysis
- Non-negative matrix completion for action detection
- Advanced Structured Prediction
- Egocentric Audio-Visual Scene Analysis : a machine learning and signal processing approach
- Unsupervised Semantic Parsing of Video Collections
- Exploitation de la supervision faible pour l'analyse des vidéos. (Leveraging weak supervision for video understanding)
- Supervised Learning Approaches for Automatic Structuring of Videos. (Méthodes d'apprentissage supervisé pour la structuration automatique de vidéos)
- Sequential Interval Network for parsing complex structured activity
- Modeling Social and Temporal Context for Video Analysis
- Maximum Margin Temporal Clustering
- Anticipating Human Activities Using Object Affordances for Reactive Robotic Response
- An Adaptive Online HDP-HMM for Segmentation and Classification of Sequential Data
- Modeling transition patterns between events for temporal human action segmentation and classification
- Fuzzy Temporal Segmentation and Probabilistic Recognition of Continuous Human Daily Activities
- ON-LINE VIDEO SEGMENTATION USING METHODS OF FAULT DETECTION IN MULTIDIMENSIONAL TIME SEQUENCES
- Structural SVM with Partial Ranking for Activity Segmentation and Classification
- A novel method for online action segmentation and classification
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