Graduate School and Research Center in Digital Sciences

Crowd context-dependent privacy protection filters

Fradi, Hajer; Eiselein, Volker; Keller, Ivo; Dugelay, Jean-Luc; Sikora, Thomas

DSP 2013, 18th International Conference on Digital Signal Processing, 1-3 July 2013, Santorini, Greece

While various privacy protection filters have been proposed in the literature, little importance has been given to the context relevance of these filters. In this paper, we specifically focus on the dependency between privacy preservation and crowd density. We show that information about the crowd density in a scene can be used in order to adjust the level of privacy protection according to the local needs. For the estimation of density maps, we use an approach based on FAST feature extraction and local optical flow computation which allow excluding feature points on the background. This process is favorable for the later density function estimation since the influence of features irrelevant to the crowd density is removed. Afterwards, we adapt the protection level of personal privacy in videos according to the crowd density. The effectiveness of the proposed framework is evaluated with videos from different crowd datasets.

Document Doi Bibtex

Title:Crowd context-dependent privacy protection filters
Keywords:Crowd density, local features, tracking, privacy filters
Department:Digital Security
Eurecom ref:3995
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Bibtex: @inproceedings{EURECOM+3995, doi = {}, year = {2013}, title = {{C}rowd context-dependent privacy protection filters}, author = {{F}radi, {H}ajer and {E}iselein, {V}olker and {K}eller, {I}vo and {D}ugelay, {J}ean-{L}uc and {S}ikora, {T}homas}, booktitle = {{DSP} 2013, 18th {I}nternational {C}onference on {D}igital {S}ignal {P}rocessing, 1-3 {J}uly 2013, {S}antorini, {G}reece }, address = {{S}antorini, {GREECE}}, month = {07}, url = {} }
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