tub-irml at mediaeval 2014 visual privacy task: privacy filtering through blurring and color...
TRANSCRIPT
Competence Center Information Retrieval & Machine Learning
TUB-IRML at MediaEval 2014 Visual Privacy Task: Privacy Filtering through Blurring and Color Remapping
Dominique Maniry, Esra Acar, Sahin Albayrak
Outline
217 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
►The Privacy Filter
►Sample Outputs of the Filter
►Discussion on the Filter
►Performance Evaluation
►Conclusions & Future Work
The Privacy Filter (1)
317 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
►Main idea: To obscure both shape and appearance of
identity-related regions through blurring and color
remapping.
►Preserve the intelligibility by
displaying edges, and
hinting anomalous events through special colors.
The Privacy Filter (2)
417 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
►The filter contains four steps:
Step 1: Blur all privacy-related regions
Step 2: Reduce number of colors & remap colors
Step 3: Apply a blending mask
Step 4: Include shape information by incorporating
edges
Step 1: Blur
517 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
Step 2: Reduce Colors
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Step 2: Remap Colors
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Step 3: Apply a Blending Mask
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►The blending mask mask(x, y) is a binary image where
annotated regions have a value of 1 and remaining
regions have a value 0.
►The smoothing is achieved by applying a Gaussian blur
to the blending mask.
Step 4: Include Shape Information (1)
917 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
►The obscured regions are overlaid with edges
obtained with Canny Edge detection.
►Edges in regions with a high privacy requirement (i.e.,
faces) are discarded.
►The remaining edges are emphasized using
morphological dilation with a 3x3 circle as structuring
element.
Step 4: Include Shape Information (2)
1017 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
A walking person Two people fighting
Sample Outputs of the Filter (1)
1117 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
Sample Outputs of the Filter (2)
1217 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
Discussion on the Filter
1317 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
Pros Cons
Parameters to tune trade-off between privacy and intelligibility (blur intensity and number of colors).
Remapped colors can convey additional information.
Different regions can have different privacy levels by using different blur intensities (e.g., face more blurred than full body).
Simple.
Identity related details can leak through shape.
Performance Evaluation (1)
1417 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
Stream 1: 230 crowd-sourcing workers. Stream 2: 65 people working at Thales (mainly in R&D).Stream 3: 59 participants from sectors including R&D, data protection and law enforcement from all around the world.
Performance Evaluation (2)
1517 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
Stream 1 Results Stream 2 Results
Stream 3 Results
Conclusions & Future Work
1617 October 2014 TUB-IRML at MediaEval 2014 Visual Privacy Task
►The user study has shown that our method is very
effective at protecting privacy.
►Future work
Evaluating different parameters to balance privacy and
intelligibility, and
Improving the appropriateness by reducing the obscured
regions using a pixel-wise segmentation.
Competence Center Information Retrieval &Machine Learning
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Esra Acar
Researcher
M.Sc.
Thanks!
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TUB-IRML at MediaEval 2014 Visual Privacy Task17 October 2014