This paper presents a method for recognizing human actions based on pose primitives. In learning mode, the parameters representing poses and activities are estimated from videos. ...
We propose a new method for human action recognition from video sequences using latent topic models. Video sequences are represented by a novel “bag-of-words” representation, w...
In this paper, we propose a novel method to establish temporal correspondence between the frames of two videos. 3D epipolar geometry is used to eliminate the distortion generated ...
This paper presents a new behavior classification system for analyzing human movements directly from video sequences. First of all, we propose a triangulation-based method to tran...
We propose a method for vision-based scene understanding in urban traffic environments that predicts the appropriate behavior of a human driver in a given visual scene. The method...
Martin Heracles, Fernando Martinelli, Jannik Frits...