View source for 17556081. METHOD OF DETERMINING VISUAL INTERFERENCE USING A WEIGHTED COMBINATION OF CIS AND DVS MEASUREMENT simplified abstract (SAMSUNG ELECTRONICS CO.,LTD.)

=METHOD OF DETERMINING VISUAL INTERFERENCE USING A WEIGHTED COMBINATION OF CIS AND DVS MEASUREMENT=


==Organization Name==

[[:Category:SAMSUNG ELECTRONICS CO.,LTD.|SAMSUNG ELECTRONICS CO.,LTD.]]


[[Category:SAMSUNG ELECTRONICS CO.,LTD.]]

==Inventor(s)==

[[:Category:SRENIVAS Varadarajan of KARNATAKA (IN)|SRENIVAS Varadarajan of KARNATAKA (IN)]][[Category:SRENIVAS Varadarajan of KARNATAKA (IN)]]

[[:Category:ANAMIKA Sharma of MADHYA PRADESH (IN)|ANAMIKA Sharma of MADHYA PRADESH (IN)]][[Category:ANAMIKA Sharma of MADHYA PRADESH (IN)]]

[[:Category:YOHAN Roh of SUWON-SI (KR)|YOHAN Roh of SUWON-SI (KR)]][[Category:YOHAN Roh of SUWON-SI (KR)]]

==METHOD OF DETERMINING VISUAL INTERFERENCE USING A WEIGHTED COMBINATION OF CIS AND DVS MEASUREMENT - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17556081 titled 'METHOD OF DETERMINING VISUAL INTERFERENCE USING A WEIGHTED COMBINATION OF CIS AND DVS MEASUREMENT

==Simplified Explanation==

The patent application describes a method for combining measurements from a dynamic vision sensor (DVS) and a contact image sensor (CIS) in an electronic device to determine visual inference. 

* The electronic device receives a DVS image and a CIS image from the image sensor.
* The device determines various parameters associated with the DVS image and the velocities of features in the CIS image.
* It calculates a confidence level for the DVS features based on the determined parameters.
* It also calculates a confidence level for the CIS features based on their velocities.
* The device then calculates a weighted visual inference by considering both the DVS feature confidence and the CIS feature confidence.

Potential applications of this technology:

* Robotics: This method can be used in robots to enhance their visual perception by combining data from different types of image sensors.
* Autonomous vehicles: By integrating DVS and CIS measurements, the technology can improve the visual inference capabilities of self-driving cars.
* Surveillance systems: The method can be applied in surveillance cameras to enhance object detection and tracking accuracy.

Problems solved by this technology:

* Combining measurements from different image sensors can provide a more comprehensive and accurate visual inference.
* The method allows for the integration of dynamic vision sensor data, which captures changes in the scene, with contact image sensor data, which provides detailed static images.
* By considering the confidence levels of both types of features, the weighted visual inference can be more reliable and robust.

Benefits of this technology:

* Improved visual perception: The combination of DVS and CIS measurements enhances the device's ability to understand and interpret visual information.
* Enhanced accuracy: By considering feature velocities and confidence levels, the weighted visual inference can provide more accurate results.
* Robustness: The method allows for reliable visual inference even in dynamic and changing environments.


==Original Abstract Submitted==

The embodiments herein provide a method of obtaining a weighted combination of dynamic vision sensor (DVS) measurements and contact image sensor (CIS) measurements for determining visual inference in an electronic device, the method includes receiving, by the electronic device, a DVS image and a CIS image from the image sensor; determining, by the electronic device, a plurality of parameters associated with the DVS image and feature velocities of a plurality of CIS features present in the CIS image; determining, by the electronic device, a determined DVS feature confidence based on the plurality of parameters associated with the DVS image; determining, by the electronic device, a determined CIS feature confidence based on the feature velocities of the plurality of features present in the CIS image; and calculating, by the electronic device, a weighted visual inference based on the determined DVS feature confidence and the determined CIS feature confidence.



[[Category:G06V10/80]]
[[Category:G06T7/246]]
[[Category:G06T7/73]]