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Activity recognition results on UCF Sports and Holywood2

Table above shows the results, obtained on UCF Sports dataset (http://crcv.ucf.edu/data/UCF_Sports_Action.php). We report recognition rate with respect to the number...


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Computational efficiency and parallel implementation

The developed algorithms are computationally effective and the compositional processing pipeline is well-suited for implementation on massively parallel architectures. Many...


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Motion hierarchy structure

Our model is comprised of three processing stages, as shown in the Figure. The task of the lowest stage (layers...


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Server crash

After experiencing a total server failure, we are back online. We apologize for the inconvenience - we are still in...


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L1: motion features

Layer L1 provides an input to the compositional hierarchy. Motion, obtained in L0 is encoded using a small dictionary.


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01234

Publication: ACCV 2012

Non-sequential multi-view detection, localization and identication of people using multi-modal feature maps

The paper describes a method for an off-line analysis of human motion using views from multiple cameras, which enables reliable localization and identification of persons without the possibility of cascading errors and total failure of the tracking. The method is based on fusion of multiple sources of visual information, where relatively basic and noisy low level features are extracted at the bottom of the hierarchy. They are processed in a manner which models increasingly complex interactions, resulting in significantly more reliable results. Acceptance rate for Asian Conference on Computer Vision in 2012: 26.8%

accv2012

 MANDELJC, Rok, KOVAČIČ, Stanislav, KRISTAN, Matej, PERŠ, Janez. Non-sequential multi-view detection, localization and identication of people using multi-modal feature maps. V: ACCV 2012. [S. l.: s. n.], 2012, str. 1-14, ilustr. [COBISS.SI-ID 9691220]

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