Abstract—In this paper, we present a method that recognizes single or multiple common actions between a pair of video sequences. We establish an energy function that evaluates geometric and photometric consistency, and solve the action recognition problem by optimizing the energy function. The proposed stochastic inference algorithm based on the Monte Carlo method explores the video pair from the local spatio-temporal interest point matches to find the common actions. Our algorithm works in unsupervised way without prior knowledge about the type and the number of common actions. Experiments show that our algorithm produces promising results on single and multiple action recognition. Keywords-computer vision; action recognition; co-recogniti...
Thesis (Ph.D.)--University of Washington, 2014We propose a system to recognize both isolated and con...
Human action recognition from videos is a chal-lenging machine vision task with multiple im-portant ...
Human action recognition and video summarization represent challenging tasks for several computer vi...
Proceedings of: 4th International Work-Conference on the Interplay Between Natural and Artificial Co...
We propose a simple but effective unsupervised learning algorithm to detect a common activity (co-ac...
This paper presents a semi-supervised method for categorizing human actions using multiple visual fe...
Human action recognition in videos draws strong research interest in computer vision because of its ...
Abstract—Action recognition is a challenging problem in video analytics due to event complexity, var...
The goal of human action recognition on videos is to determine in an automatic way what is happening...
Recently a lot of progress has been made in the field of video segmentation. The question then arise...
One of the most exciting and useful computer vision research topics is automated human activity iden...
In this paper, we make three main contributions in the area of action recognition: (i) We introduce ...
This paper deals with human action classification by utilizing spatio-temporal (ST) co-occurrences b...
Two-view methods have been well developed to identify human actions. However, in a case where the co...
When the camera viewing an action is moving, the motion observed in the video not only contains the ...
Thesis (Ph.D.)--University of Washington, 2014We propose a system to recognize both isolated and con...
Human action recognition from videos is a chal-lenging machine vision task with multiple im-portant ...
Human action recognition and video summarization represent challenging tasks for several computer vi...
Proceedings of: 4th International Work-Conference on the Interplay Between Natural and Artificial Co...
We propose a simple but effective unsupervised learning algorithm to detect a common activity (co-ac...
This paper presents a semi-supervised method for categorizing human actions using multiple visual fe...
Human action recognition in videos draws strong research interest in computer vision because of its ...
Abstract—Action recognition is a challenging problem in video analytics due to event complexity, var...
The goal of human action recognition on videos is to determine in an automatic way what is happening...
Recently a lot of progress has been made in the field of video segmentation. The question then arise...
One of the most exciting and useful computer vision research topics is automated human activity iden...
In this paper, we make three main contributions in the area of action recognition: (i) We introduce ...
This paper deals with human action classification by utilizing spatio-temporal (ST) co-occurrences b...
Two-view methods have been well developed to identify human actions. However, in a case where the co...
When the camera viewing an action is moving, the motion observed in the video not only contains the ...
Thesis (Ph.D.)--University of Washington, 2014We propose a system to recognize both isolated and con...
Human action recognition from videos is a chal-lenging machine vision task with multiple im-portant ...
Human action recognition and video summarization represent challenging tasks for several computer vi...