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Trajectory-based human activity recognition aims at understanding human behaviors in video sequences. Some existing approaches to this problem, e.g., hidden Markov models (HMM), have a severe limitation, namely the number of motions has to be preset. In fact, this number is difficult to define in advance in real practice. To overcome this shortcoming, we propose a new method for modeling human trajectories...
In this paper we consider a class of stationary problem of stochastic control of impulse type, of which the state process is a solution to a process generated by a stochastic differential equation with drift factor. We also prove the existence of optimal impulse control. Moreover, we construct an optimal control and determine the optimal control area.
In the domain adaptation research, which recently becomes one of the most important research directions in machine learning, source and target domains are with different underlying distributions. In this paper, we propose an ensemble learning framework for domain adaptation. Owing to the distribution differences between source and target domains, the weights in the final model are sensitive to target...
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