Abstract. This paper describes daily life activity recognition using wearable acceleration sensors attached to four different parts of the human body. The experimental data set con...
Social applications on the web let users track and follow the activities of a large number of others regardless of location or affiliation. There is a potential for this transpare...
Laura A. Dabbish, H. Colleen Stuart, Jason Tsay, J...
In this paper, a novel weightlessness feature for activity recognition from a tri-axial acceleration signals have been proposed. Since the orientation between accelerometer and us...
Scarcity and infeasibility of human supervision for large
scale multi-class classification problems necessitates active
learning. Unfortunately, existing active learning methods
...
Prateek Jain (University of Texas at Austin), Ashi...
We present an activity recognition feature inspired by
human psychophysical performance. This feature is based
on the velocity history of tracked keypoints. We present a
generat...