Method and device for facilitating a privacy-aware representation in a system
Embodiments herein disclose a method for facilitating a privacy-aware representation in a system. The method comprises determining using a content analyzer a layout of a scene. Thereafter, one or more objects in the scene is identified using the content analyzer to define a relationship between the objects. A privacy status to be tagged to the one or more identified objects is inferred by using a machine learning model. At least one object is processed based on the privacy status inferred. A privacy-aware representation of the scene is rendered, wherein the privacy-aware representation displays the scene with at least one processed object.
1 . A computer-implemented method for facilitating a privacy-aware representation in a system, the method comprising:
determining, using a content analyzer, a layout of a scene, wherein the scene is received through a user input device and the scene comprises a set of objects with varying privacy requirements;
identifying, using the content analyzer, at least a first object in the scene and a second object in the scene;
determining a relationship between the first object and the second object;
inputting to a machine learning model relationship information indicating the determined relationship between the first object and second object;
after inputting the relationship information to the machine learning model, obtaining from the machine learning model privacy information indicating an inferred privacy status for the first object;
processing the first object based on the inferred privacy status to produce a first processed object; and
rendering a privacy-aware representation of the scene, wherein the privacy-aware representation displays the scene with at least the first processed object.
2 . The method of claim 1 , wherein processing the first object comprises one of: partially concealing the first object, completely concealing the first object, transforming the first object, or transforming an area around the first object.
3 . The method of claim 1 , wherein the method further comprises:
obtaining a receiver's preferences about the first processed object from the privacy-aware representation through a point of interest module.
4 . The method of claim 3 , wherein the point of interest module comprises one or more sensors to capture the receiver's eyes gaze, tactile movements, or touch.
5 . The method of claim 3 , wherein the method further comprises:
providing the receiver's preferences to a sender;
receiving an input from the sender in response to the receiver's preferences; and
defining a user action based on the input from the sender, by the machine learning model to process the first object.
6 . The method of claim 1 , wherein the method further comprises configuring the machine learning model in a training phase with the first object as input to define a state of the first object, wherein the state indicates an existing privacy status associated with the first object.
7 . The method of claim 1 , wherein the method further comprises configuring the machine learning model in a training phase to predict an action to process the first object.
8 . The method of claim 1 , wherein the method further comprises configuring the machine learning model in a training phase to iteratively update the state and action associated with the first object based on the user action.
9 . The method of claim 1 , wherein the method further comprises configuring the machine learning model to calculate a reward, r, which enables an agent to predict an action similar to a user action by minimizing or maximizing a difference between a predicted action and the user action using a weight factor per object.
10 . The method of claim 1 , wherein the machine learning model is trained using one a reinforcement learning algorithm, an unsupervised machine learning, and a Q-learning algorithm.
11 . The method of claim 1 , wherein the scene comprises at least one of an image content, audio-visual content and an audio content.
12 . The method of claim 1 , wherein the user input device is one of a camera, a speaker, a headphone, a network node, a tactile device or any device capable of controlling a sensory actuator.
13 . The method of claim 1 , wherein the system is at least one of a wearable device, a hand-held device, a distributed computing system, or computing device configured to render mixed reality, augmented reality, extended reality, or virtual reality.
14 . A non-transitory computer readable storage medium storing a computer program comprising instructions which when executed by a processing unit of the system causes the system to perform the method of claim 1 .
15 . A system for facilitating a privacy-aware representation, the system comprising:
memory; and
processing circuitry, wherein the system is configured to perform a method comprising:
determining, using a content analyzer, a layout of a scene, wherein the scene is received through a user input device and the scene comprises a set of objects with varying privacy requirements;
identifying, using the content analyzer, at least a first object in the scene and a second object in the scene;
determining a relationship between the first object and the second object;
inputting to a machine learning model relationship information indicating the determined relationship between the first object and second object;
after inputting the relationship information to the machine learning model, obtaining from the machine learning model privacy information indicating an inferred privacy status for the first object;
processing the first object based on the inferred privacy status to produce a first processed object; and
rendering a privacy-aware representation of the scene, wherein the privacy-aware representation displays the scene with at least the first processed object.