Kinematic-Layout-aware Random Forests for Depth-based Action Recognition.
Seungryul BaekZhiyuan ShiMasato KawadeTae-Kyun KimPublished in: BMVC (2017)
Keyphrases
- action recognition
- random forests
- depth sensors
- depth images
- depth cameras
- random forest
- action recognition in videos
- ensemble methods
- decision trees
- bag of words
- logistic regression
- machine learning algorithms
- human actions
- activity recognition
- body parts
- action classification
- recognition of human actions
- human pose
- computer vision
- human activities
- recognizing human actions
- decision tree ensembles
- depth map
- recognizing actions
- prediction accuracy
- depth data
- bag of features
- machine learning