Placing numerous data objects and their corresponding labels in limited screen space is a challenging problem in information visualization systems. Extending map-oriented techniqu...
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...
This paper presents a framework for view-invariant action recognition in image sequences. Feature-based human detection becomes extremely challenging when the agent is being observ...
Bhaskar Chakraborty, Marco Pedersoli, Jordi Gonz&a...
Scene labeling research has mostly focused on outdoor scenes, leaving the harder case of indoor scenes poorly understood. Microsoft Kinect dramatically changed the landscape, show...
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...