In this paper we present a new video object trajectory clustering algorithm, which allows us to model and analyse the patterns of object behaviors based on the extracted features using tensor analysis. The proposed algorithm consists of three steps as follows: extraction of trajectory features by tensor analysis, non-parametric probabilistic mean shift clustering and clustering correction. The performance of the proposed algorithm is evaluated on standard data-sets and compared with classical techniques
International audienceIt is well known that video cameras provide one of the richest, and most promi...
Abstract. A new technique is proposed for clustering and similarity retrieval of video motion clips ...
Abstract. Scene understanding corresponds to the real time process of perceiving, analysing and elab...
In this paper we present a new video object trajectory clustering algorithm, which allows us to mode...
Surveillance camera usage has increased significantly for visual surveillance. Manual analysis of la...
Dense trajectories has been shown as a very promising method in the human action recognition area. ...
k-means algorithm is one of the basic clustering techniques that is used in many data mining applica...
A system is described that tracks moving objects in a video dataset so as to extract a representatio...
Techniques for understanding video object motion activity are becoming increasingly important with t...
International audienceThis work aims to identify abnormal behaviors from the analysis of humans or v...
International audienceThis work aims to identify abnormal behaviors from the analysis of humans or v...
We present a deep trajectory feature representation approach to aid trajectory clustering and motion...
Abstract. In this paper, we present a framework for visual object track-ing based on clustering traj...
ABSTRACT Today portable devices as mobile phones, laptops, personal digital assistants(PDAs), and ...
Abstract—This paper presents a novel technique for clustering of video motion clips using coefficien...
International audienceIt is well known that video cameras provide one of the richest, and most promi...
Abstract. A new technique is proposed for clustering and similarity retrieval of video motion clips ...
Abstract. Scene understanding corresponds to the real time process of perceiving, analysing and elab...
In this paper we present a new video object trajectory clustering algorithm, which allows us to mode...
Surveillance camera usage has increased significantly for visual surveillance. Manual analysis of la...
Dense trajectories has been shown as a very promising method in the human action recognition area. ...
k-means algorithm is one of the basic clustering techniques that is used in many data mining applica...
A system is described that tracks moving objects in a video dataset so as to extract a representatio...
Techniques for understanding video object motion activity are becoming increasingly important with t...
International audienceThis work aims to identify abnormal behaviors from the analysis of humans or v...
International audienceThis work aims to identify abnormal behaviors from the analysis of humans or v...
We present a deep trajectory feature representation approach to aid trajectory clustering and motion...
Abstract. In this paper, we present a framework for visual object track-ing based on clustering traj...
ABSTRACT Today portable devices as mobile phones, laptops, personal digital assistants(PDAs), and ...
Abstract—This paper presents a novel technique for clustering of video motion clips using coefficien...
International audienceIt is well known that video cameras provide one of the richest, and most promi...
Abstract. A new technique is proposed for clustering and similarity retrieval of video motion clips ...
Abstract. Scene understanding corresponds to the real time process of perceiving, analysing and elab...