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This work presents a dictionary learning algorithm for developing a part-based trajectory representation, which combines merits of the existing Markovian-based ...
This work presents a dictionary learning algorithm for developing a part- based trajectory representation, which combines merits of the existing Markovian-based ...
This work presents the augmented semi-nonnegative sparse coding (ASNSC) algorithm for solving a constrained dictionary learning problem, and shows that the ...
This work presents a dictionary learning algorithm for developing a part-based trajectory representation, which combines merits of the existing Markovian-based ...
This work presents a dictionary learning algorithm for developing a part-based trajectory representation, which combines merits of the existing Markovian-based ...
Holdings: Augmented dictionary learning for motion prediction
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Developing accurate models and efficient representations of multivariate trajectories is important for understanding the behavior patterns of mobile agents.
This paper proposes two algorithms for learning incoherent dictionaries in an offline and online manner by extending the offline augmented semi-non-negative ...
Oct 29, 2022 · This paper proposes two algorithms for learning incoherent dictionaries in an offline and online manner by extending the offline augmented semi-non-negative ...
To solve this problem, this paper proposes two algorithms for learning incoherent dictionaries in an offline and online manner by extending the offline ...
Augmented Dictionary Learning for Motion Prediction. Y Chen, M Liu, J How. The International Conference on Robotics and Automation, 2527 - 2534, 2016. 33, 2016.