A Probabilistic Approach for Human Everyday Activities Recognition using Body Motion from RGB-D Images

Keyphrases

• 3D Motion 50%
• 3D Skeleton 50%
• Activity Classification 50%
• Activity Datasets 50%
• Activity Recognition 100%
• Assisted Living 50%
• Bayesian Mixture Model 100%
• Benchmark Dataset 50%
• Body Motion 100%
• Current Frame 50%
• Depth Perception 50%
• Dynamic Bayesian 100%
• Elderly Care 50%
• Everyday Activities 100%
• Frame Classification 50%
• Human Activities 100%
• Human Behavior Recognition 50%
• Human Body Motion 50%
• Human-robot Interaction 50%
• Learning Classifiers 50%
• Multiple Classifier System 50%
• Multiple Learning 50%
• Overall Accuracy 50%
• Posterior Probability 50%
• Precision Accuracy 50%
• Precision-recall 50%
• Prior Probability 50%
• Probabilistic Approach 100%
• Probabilistic Inference 50%
• Publicly Available 50%
• Recall Accuracy 50%
• RGB-D 100%
• Skeleton Features 50%
• State-of-the-art Techniques 50%
• Uncertainty Measure 50%

Computer Science

• Activity Recognition 100%
• Human Robot Interaction 50%
• multiple classifier 50%
• Posterior Probability 50%
• Prior Probability 50%
• Probabilistic Approach 100%
• Probabilistic Inference 50%
• Related Feature 50%
• Reported Result 50%
• RGB-D Image 100%
• Temporal Information 50%