7,736 research outputs found
Pooling-Invariant Image Feature Learning
Unsupervised dictionary learning has been a key component in state-of-the-art
computer vision recognition architectures. While highly effective methods exist
for patch-based dictionary learning, these methods may learn redundant features
after the pooling stage in a given early vision architecture. In this paper, we
offer a novel dictionary learning scheme to efficiently take into account the
invariance of learned features after the spatial pooling stage. The algorithm
is built on simple clustering, and thus enjoys efficiency and scalability. We
discuss the underlying mechanism that justifies the use of clustering
algorithms, and empirically show that the algorithm finds better dictionaries
than patch-based methods with the same dictionary size
Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories
With the explosion in the availability of spatio-temporal tracking data in
modern sports, there is an enormous opportunity to better analyse, learn and
predict important events in adversarial group environments. In this paper, we
propose a deep decision tree architecture for discriminative dictionary
learning from adversarial multi-agent trajectories. We first build up a
hierarchy for the tree structure by adding each layer and performing feature
weight based clustering in the forward pass. We then fine tune the player role
weights using back propagation. The hierarchical architecture ensures the
interpretability and the integrity of the group representation. The resulting
architecture is a decision tree, with leaf-nodes capturing a dictionary of
multi-agent group interactions. Due to the ample volume of data available, we
focus on soccer tracking data, although our approach can be used in any
adversarial multi-agent domain. We present applications of proposed method for
simulating soccer games as well as evaluating and quantifying team strategies.Comment: To appear in 4th International Workshop on Computer Vision in Sports
(CVsports) at CVPR 201
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