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Video sequences contain rich dynamic patterns, such as dynamic texture patterns that exhibit stationarity in the temporal domain, and action patterns that are non-stationary in either spatial or temporal domain. We show that a spatial-temporal generative ConvNet can be used to model and synthesize dynamic patterns. The model defines a probability distribution on the video sequence, and the log probability...
This paper presents a method for learning an And-Or model to represent context and occlusion for car detection and viewpoint estimation. The learned And-Or model represents car-to-car context and occlusion configurations at three levels: (i) spatially-aligned cars, (ii) single car under different occlusion configurations, and (iii) a small number of parts. The And-Or model embeds a grammar for representing...
We study the problem of automatically learning event AND-OR grammar from videos of a certain environment, e.g. an office where students conduct daily activities. We propose to learn the event grammar under the information projection and minimum description length principles in a coherent probabilistic framework, without manual supervision about what events happen and when they happen. Firstly a predefined...
This Paper deeply analyzes and studies the existing problems in the any cast communication models in an IPv6 network and proposes a k-Any cast routing schemes for IPv6 network which are fault tolerance, load balancing, security, and improvement in system performance. In addition, this paper proposes a concrete scheme on how to implement this k-Any cast communication model in an IPv6 network which...
Human-robot interaction (HRI) is an important topic in robotics, especially in assistive robotics. Here we propose a smart assisted living (SAIL) system to help elderly people, patients, and the disabled. In this paper, we address the human intention recognition problem and design a hidden Markov models (HMM) based online recognition algorithm to classify hand gestures. The data is collected by a...
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