Visual Privacy by Context:A Level-Based Visualisation

Scheme

José R. Padilla-López, Alexandros A. Chaaraoui and Francisco Flórez-Revuelta

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Protection methods

Naïve Blurring Pixelating Emboss

Silhouette / Masking Skeleton 3D Avatar Invisibility

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Why (visual) privacy?

AAL services provide help to people in need of long-term care.

Development of novel video-based AAL services for private spaces.

Some AAL services may require human access to video stream.

...

...

...

Long-term analysis

Setup and Profiles DB (Activities, Inhabitants, Objects, ...)

Log

Alarm Actuators

Event

Caregiver

Camera 1 Camera 2 Camera N

Motion Detection

Motion Detection

Motion Detection

Human Behaviour

Analysis

Human Behaviour

Analysis

Human Behaviour

Analysis

Multi-view Human Behaviour Analysis

Environmental Sensor Information

Reasoning System

Privacy

Architecture of our Intelligent Monitoring System

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but... What is privacy?

Privacy: Sphere of the private life that an individual has right to protect from intruders.

However...

The notion of privacy is highly subjective. It depends on the individual.

Several factors are involved:

● The private “thing”

● Observer / intruder

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The private “thing”

“A picture is worth a thousand words”

An image conveys the following information about individuals:

● Identity (Who?)

● Appearance (How?)

● Location (Where?)

● Activity / Behaviour (What?)

● Time (When?)

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How to ensure (visual) privacy?

But...

● Image must retain its utility

● A trade-off between privacy protection and image utility is needed

● Privacy must be adaptable to the individual

Image Redaction: Modify an image or a sequence of images so as to protect objects (visual clues) appearing on them.

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Privacy by Context

● We propose a privacy protection scheme that is aware of the context

● A set of redaction methods is used

● A context describes “any” situation.

● Users provide their privacy preferences by linking instances of the context with protection methods

Blur

Pixel

Emboss

Silhouette

Skeleton Avatar 3D

Naïve

Invisibility

Selected Method Skeleton

Set of redaction methods

User-given Matching

Context Composed of several

variables

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Used Context

● The observer / viewer / watcher

● Identity of the person (to retrieve the privacy profile)

● Closeness between person and observer (e.g. relative, doctor, acquaintance, … )

● Appearance (dressed?)

● Location (e.g. kitchen)

● Event (e.g. cooking, watching TV, fall, ...)

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Redaction methods

Demo

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Conclusions

● Visual Privacy by Context covers several research fields Computer vision (HBA, Object detection, Person Re-id, …), Image processing and in-painting, AI, Sociology.

● As privacy is highly subjective, any solution should be adaptable to each individual

● Need of a privacy measure so as to objectively evaluate protection methods

Thank you for your attention

Questions?