18180039. SIGNATURE-BASED OBJECT TRACKING IN VIDEO FEED simplified abstract (Microsoft Technology Licensing, LLC)

From WikiPatents
Jump to navigation Jump to search

SIGNATURE-BASED OBJECT TRACKING IN VIDEO FEED

Organization Name

Microsoft Technology Licensing, LLC

Inventor(s)

Sudhanshu Uday Sohoni of Bothell WA (US)

SIGNATURE-BASED OBJECT TRACKING IN VIDEO FEED - A simplified explanation of the abstract

This abstract first appeared for US patent application 18180039 titled 'SIGNATURE-BASED OBJECT TRACKING IN VIDEO FEED

Simplified Explanation

A device calculates signatures for regions of video frames to detect objects of interest.

  • The device calculates a signature for a region of a video frame based on its content.
  • The signature is calculated for a detected object of interest within the video feed.
  • The device compares signatures between consecutive frames to determine differences.
  • If the difference exceeds a threshold, the device triggers object detection on the video feed.

Potential Applications

This technology can be applied in:

  • Video surveillance systems
  • Object tracking in videos
  • Automated security systems

Problems Solved

This technology helps in:

  • Efficient object detection in video feeds
  • Real-time monitoring of objects of interest
  • Enhancing security measures through automated detection

Benefits

The benefits of this technology include:

  • Improved accuracy in object detection
  • Faster response to potential threats
  • Enhanced surveillance capabilities

Potential Commercial Applications

The potential commercial applications of this technology include:

  • Security companies offering advanced surveillance solutions
  • Video analytics companies providing object tracking services
  • Integration into smart home security systems

Possible Prior Art

One possible prior art for this technology could be the use of signature-based object detection in image processing systems.

Unanswered Questions

How does the device handle changes in lighting conditions that may affect the signatures?

The device may need to incorporate algorithms to adapt to varying lighting conditions and ensure accurate object detection.

What is the computational overhead of calculating signatures for each region of interest in the video frames?

The device may need to optimize its processing power to handle the calculations efficiently without causing delays in object detection.


Original Abstract Submitted

A device may calculate a first signature for a first region of a first video frame of a video feed based on content of the first video frame. The first region is associated with a detected object of interest within the video feed. The device may calculate a second signature for a second region of a second video frame of the video feed based on content of the second video frame. The second video frame is subsequent to the first video frame within the video feed, and the second region is associated with the detected object of interest within the video feed. The device may determine a measure of difference between the first signature and the second signature. Based on the amount of difference between the first signature and the second signature exceeding a threshold, the device may trigger a signature-based object detection on the video feed.