کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
410777 | 679162 | 2008 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Activity recognition through multi-scale motion detail analysis Activity recognition through multi-scale motion detail analysis](/preview/png/410777.png)
Activity recognition is one of the most challenging problems in the video content analysis and high-level computer vision. This paper proposes a novel activity recognition approach in which we decompose an activity into multiple interactive stochastic processes, each corresponding to one scale of motion details. For modeling the interactive processes, we present a hierarchical durational-state dynamic Bayesian network (HDS-DBN) to model two stochastic processes which are related to two appropriate scales in intelligent surveillance. In HDS-DBN, states are decomposed in terms of multi-scale motion details, and each kind of state indicates legible meaning. The effectiveness of this approach is demonstrated by experiments of individual activity recognition and two-person interacting activity recognition.
Journal: Neurocomputing - Volume 71, Issues 16–18, October 2008, Pages 3561–3574