Intel corporation (20240127061). VIDEO SUMMARIZATION USING SEMANTIC INFORMATION simplified abstract
Contents
- 1 VIDEO SUMMARIZATION USING SEMANTIC INFORMATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 VIDEO SUMMARIZATION USING SEMANTIC INFORMATION - 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 Original Abstract Submitted
VIDEO SUMMARIZATION USING SEMANTIC INFORMATION
Organization Name
Inventor(s)
Myung Hwangbo of Lake Oswego OR (US)
Krishna Kumar Singh of Davis CA (US)
Teahyung Lee of Chandler AZ (US)
Omesh Tickoo of Portland OR (US)
VIDEO SUMMARIZATION USING SEMANTIC INFORMATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240127061 titled 'VIDEO SUMMARIZATION USING SEMANTIC INFORMATION
Simplified Explanation
The patent application describes an apparatus that uses a machine learning algorithm to process images from a video segment and determine scores based on detected actions associated with labels.
- The apparatus processes a first image from a video segment using a machine learning algorithm to determine a score.
- The algorithm detects actions associated with images and labels them accordingly.
- The apparatus calculates a second score for the video segment based on the scores of individual images.
- Based on the second score, the apparatus decides whether to retain the video segment in memory.
Potential Applications
This technology could be applied in video surveillance systems to automatically detect and classify actions in real-time.
Problems Solved
This technology solves the problem of efficiently analyzing large amounts of video data by automating the process of detecting and categorizing actions.
Benefits
The benefits of this technology include improved video analysis accuracy, reduced manual labor in reviewing video footage, and faster response times to potential security threats.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of advanced video analytics software for security companies.
Possible Prior Art
Prior art in this field may include existing video analytics software that uses machine learning algorithms to analyze video content for specific actions and events.
Unanswered Questions
This article does not address the potential privacy implications of using machine learning algorithms to analyze video content.
What are the computational requirements for implementing this technology in real-time video processing systems?
The article does not provide information on the computational resources needed to deploy this technology for real-time video processing applications.
Original Abstract Submitted
example apparatus disclosed herein are to process a first image of a first video segment from the image capture sensor with a machine learning algorithm to determine a first score for the first image, the machine learning algorithm to detect actions associated with images, the actions associated with labels. disclosed example apparatus are also to determine a second score for the first video segment based on respective first scores for corresponding images in the first video segment. disclosed example apparatus are further to determine, based on the second score, whether to retain the first video segment in the memory.
