— Intention recognition is an important topic in human-robot cooperation that can be tackled using probabilistic model-based methods. A popular instance of such methods are Bayes...
Oliver C. Schrempf, David Albrecht, Uwe D. Hanebec...
Action recognition is one of the most active research fields in computer vision. In this paper, we propose a novel method for classifying human actions in a series of image seque...
We propose a method for recognizing human actions in videos. Inspired from the recent bag-of-words approaches, we represent actions as documents consisting of words, where a word ...
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
The paper introduces an action recognition framework that uses concepts from the theory of chaotic systems to model and analyze nonlinear dynamics of human actions. Trajectories o...
Real-world actions occur often in crowded, dynamic environments. This poses a difficult challenge for current approaches to video event detection because it is difficult to segmen...
We address recognition and localization of human actions in realistic scenarios. In contrast to the previous work studying human actions in controlled settings, here we train and ...
In this paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...
Visual recognition of human actions in video clips has been an active field of research in recent years. However, most published methods either analyse an entire video and assign ...
We present a novel model for human action categorization. A video sequence is represented as a collection of spatial and spatial-temporal features by extracting static and dynamic...