Microsoft technology licensing, llc (20240129497). Reduced Video Stream Resource Usage simplified abstract
Contents
- 1 Reduced Video Stream Resource Usage
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Reduced Video Stream Resource Usage - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
Reduced Video Stream Resource Usage
Organization Name
microsoft technology licensing, llc
Inventor(s)
Anthony C. Romano of Lebanon TN (US)
Naiteek Sangani of Bothell WA (US)
Ryan S. Menezes of Bellevue WA (US)
Reduced Video Stream Resource Usage - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240129497 titled 'Reduced Video Stream Resource Usage
Simplified Explanation
The patent application describes a resource-aware object detection system for encoded video streams that can identify frames containing a specific object without decoding the frames.
- This innovation allows for efficient object detection in video streams without the need to fully decode each frame.
- The system can identify frames with objects of interest, such as humans, based on encoded data, saving computational resources.
- By detecting objects in encoded video streams, this technology can improve real-time video analysis and surveillance applications.
Potential Applications
The technology can be applied in various fields such as:
- Video surveillance systems
- Video analytics for security purposes
- Automated object tracking in videos
Problems Solved
The technology addresses the following issues:
- Resource-intensive object detection in video streams
- Real-time identification of objects without full frame decoding
- Efficient utilization of computational resources for video analysis
Benefits
The benefits of this technology include:
- Improved efficiency in object detection in video streams
- Reduced computational load for real-time video analysis
- Enhanced accuracy in identifying objects of interest
Potential Commercial Applications
The technology can be commercially applied in:
- Security and surveillance industries
- Video analytics software development
- Smart city infrastructure for monitoring and analysis
Possible Prior Art
One possible prior art could be the use of motion detection algorithms in video surveillance systems to identify objects of interest without fully decoding video frames.
Unanswered Questions
How does the system handle different types of objects in the video stream?
The system likely uses object recognition algorithms to detect various types of objects based on predefined models and features.
What is the impact of the technology on video streaming services?
The technology could potentially improve video streaming services by enabling more efficient object detection and analysis without significant computational overhead.
Original Abstract Submitted
the description relates to resource aware object detection for encoded video streams that can identify frames of the video stream that include an object of interest, such as a human, without decoding the frames.
