Poster ACM Multimedia 2013
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1. Fisher Kernel Theory Time Matters! Capturing Variation in Time in Video using Fisher Kernels Ionuț Mironică, Jasper Uijlings, Bogdan Ionescu, Negar Rostamzadeh, Nicu Sebe 1 2 1, 2 LAPI – University „POLITEHNICA” Bucharest, 061071, Romania MHUG DISI – University of Trento, Italy 2 2 2 1 Variation in distance to clusters center Variation in distance to cluster centre represents a signal as the gradient of the probability density function that is a learned generative model of that signal combines the benefits of generative and discriminative approaches Temporal order is lost but subtle variations in time within a cluster drastic variations in tim by different clusters 2. Fisher Kernel Framework 3. Experimental Results Conclusion: State-of-the-art results or better using cheaper features! ediaEval 2012 dataset- Genre Retrieval ADL dataset - Daily Activities UCF dataset – Sport Recognition
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Transcript of Poster ACM Multimedia 2013
1. Fisher Kernel Theory
Time Matters!Capturing Variation in Time in Video using Fisher
KernelsIonuț Mironică, Jasper Uijlings, Bogdan Ionescu, Negar Rostamzadeh, Nicu Sebe
1 21,2
LAPI – University „POLITEHNICA” Bucharest, 061071, RomaniaMHUG DISI – University of Trento, Italy
2 2
21
Variation in distance to clusters center
Variation in distance to cluster centre
represents a signal as the gradient of the probability density function that is a learned generative model of that signal
combines the benefits of generative and discriminative approaches
Temporal order is lost
but
subtle variations in timewithin a cluster
drastic variations in timeby different clusters
2. Fisher Kernel Framework
3. Experimental Results
Conclusion: State-of-the-art results or better using cheaper features!
MediaEval 2012 dataset- Genre Retrieval ADL dataset - Daily Activities UCF dataset – Sport Recognition
