This paper analyzes the movements of the human body limbs (hands, feet and head) and center of gravity in order to detect simple actions such as walking, jumping and displacing an...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
We present a compact representation for human action recognition in videos using line and optical flow histograms. We introduce a new shape descriptor based on the distribution of...
Nazli Ikizler, Pinar Duygulu, Ramazan Gokberk Cinb...
We present an algorithm for detecting human actions
based upon a single given video example of such actions.
The proposed method is unsupervised, does not require
learning, segm...
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of joint positions or pose angles. Such recognition is d...