Spatio-Temporal Proximity Distribution Kernels for Action Recognition

No abstract is available for this paper.

• Publication year

  2010

• Venue

  IEEE International Conference on Acoustics, Speech, and Signal Processing

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/ICASSP.2010.5495360
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Human Action Recognition under Log-Euclidean Riemannian Metric

  2009cited by this paper
• Directed Markov Stationary Features for visual classification

  2009influential reference
• Universal and Adapted Vocabularies for Generic Visual Categorization

  2008cited by this paper
• Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words

  2008cited by this paper
• Action recognition by learning mid-level motion features

  2008cited by this paper
• Recognizing human actions using multiple features

  2008cited by this paper
• One step beyond histograms: Image representation using Markov stationary features

  2008influential reference
• Human action recognition using Local Spatio-Temporal Discriminant Embedding

  2008cited by this paper
• Learning realistic human actions from movies

  2008cited by this paper
• Spatial-Temporal correlatons for unsupervised action classification

  2008cited by this paper
• Proximity Distribution Kernels for Geometric Context in Category Recognition

  2007cited by this paper
• Tensor Canonical Correlation Analysis for Action Classification

  2007cited by this paper
• Graph Based Discriminative Learning for Robust and Efficient Object Tracking

  2007cited by this paper
• Recognizing Human Activities from Silhouettes: Motion Subspace and Factorial Discriminative Graphical Model

  2007cited by this paper
• Successive Convex Matching for Action Detection

  2006cited by this paper
• (2D)2PCA: Two-directional two-dimensional PCA for efficient face representation and recognition

  2005cited by this paper
• Behavior recognition via sparse spatio-temporal features

  2005cited by this paper
• Recognizing human actions: a local SVM approach

  2004cited by this paper

• No citing papers are available for this paper.