View source for Nvidia corporation (20240112356). ESTIMATING FLOW VECTORS FOR OCCLUDED CONTENT IN VIDEO SEQUENCES simplified abstract

=ESTIMATING FLOW VECTORS FOR OCCLUDED CONTENT IN VIDEO SEQUENCES=


==Organization Name==

[[:Category:nvidia corporation|nvidia corporation]]


[[Category:nvidia corporation]]

==Inventor(s)==

[[:Category:Karthick Sekkappan of Pune (IN)|Karthick Sekkappan of Pune (IN)]][[Category:Karthick Sekkappan of Pune (IN)]]

[[:Category:Aurobinda Maharana of Chinchwad (IN)|Aurobinda Maharana of Chinchwad (IN)]][[Category:Aurobinda Maharana of Chinchwad (IN)]]

[[:Category:Vipul Parashar of Pune (IN)|Vipul Parashar of Pune (IN)]][[Category:Vipul Parashar of Pune (IN)]]

==ESTIMATING FLOW VECTORS FOR OCCLUDED CONTENT IN VIDEO SEQUENCES - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240112356 titled 'ESTIMATING FLOW VECTORS FOR OCCLUDED CONTENT IN VIDEO SEQUENCES

==Simplified Explanation==

The patent application describes systems and methods for estimating optical flow vectors for occluded pixels in a video sequence, identifying regions of occluded pixels, and determining the cause of occlusion. Different estimation techniques are applied based on the cause of occlusion to provide a lightweight estimation of optical flow data.

* Estimation of optical flow vectors for pixels occluded due to movement out of a frame is done using a first technique.
* Estimation of optical flow vectors for pixels occluded due to foreground movement is done using a second technique.

== Potential Applications ==
This technology can be applied in various fields such as video surveillance, autonomous driving, augmented reality, and robotics.

== Problems Solved ==
1. Improved estimation of optical flow vectors for occluded pixels.
2. Efficient identification and handling of occluded regions in video sequences.

== Benefits ==
1. Enhanced accuracy in estimating optical flow data.
2. Reduced computational resources required for optical flow estimation.
3. Better understanding of occlusion causes in video sequences.

== Potential Commercial Applications ==
Optical flow estimation software for video editing applications.
Real-time object tracking systems for security and surveillance.
Autonomous vehicle navigation systems for obstacle detection and avoidance.

== Possible Prior Art ==
One possible prior art could be the use of traditional optical flow estimation techniques that do not specifically address occluded pixels and their causes.

=== What are the limitations of the proposed system in handling complex occlusion scenarios? ===

The proposed system may struggle with highly dynamic scenes where multiple objects occlude each other simultaneously, leading to challenges in accurately estimating optical flow vectors for all occluded pixels.

=== How does the proposed system compare to existing methods in terms of computational efficiency? ===

The proposed system aims to provide a lightweight and less resource-intensive estimation of optical flow data compared to traditional methods, making it more efficient for real-time applications.


==Original Abstract Submitted==

systems and methods estimate optical flow vectors for occluded pixels between frames of a video sequence. regions of occluded pixels may be identified and a cause of their occlusion may be determined. different estimation techniques may be applied based, at least in part, on the cause of occlusion to provide a lightweight, less resource intensive estimation of optical flow data. optical flow vectors for pixels that are occluded due to movement out of a frame may be estimated using a first technique while optical flow vectors for pixels that are occluded due to foreground movement may be estimated using a second technique.



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