Apple inc. (20240119699). DETECTION OF MOMENT OF PERCEPTION simplified abstract

DETECTION OF MOMENT OF PERCEPTION

Organization Name

apple inc.

Inventor(s)

Hessam Bagherinezhad of Seattle WA (US)

Carlo Eduardo Cabanero Del Mundo of Seattle WA (US)

Anish Jnyaneshwar Prabhu of Seattle WA (US)

Peter Zatloukal of Seattle WA (US)

Lawrence Frederick Arnstein of Seattle WA (US)

DETECTION OF MOMENT OF PERCEPTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240119699 titled 'DETECTION OF MOMENT OF PERCEPTION

Simplified Explanation

The method described in the abstract involves using a machine-learning model to classify image frames in a video to identify a moment of perception of a determined motion associated with an object of interest.

• Motion associated with object of interest is determined based on image frames
• Machine-learning model is used to classify image frames in the video
• Identify a moment of perception of the determined motion

Potential Applications

This technology could be applied in various fields such as surveillance, sports analysis, and human-computer interaction.

Problems Solved

This technology helps in automatically detecting and analyzing specific motions in videos, which can be time-consuming and challenging for humans to do manually.

Benefits

The technology provides a more efficient and accurate way to analyze motion in videos, leading to improved understanding and interpretation of visual data.

Potential Commercial Applications

• Video surveillance systems
• Sports performance analysis software
• Human-computer interaction tools

Possible Prior Art

There may be existing technologies or methods that involve analyzing motion in videos using machine learning models, but specific prior art would need to be researched to determine any overlap with this particular innovation.

What are the limitations of this technology in real-world applications?

This technology may face challenges in accurately identifying complex motions or in scenarios with poor video quality.

How does this technology compare to traditional methods of analyzing motion in videos?

This technology offers a more automated and efficient approach compared to manual methods, saving time and potentially improving accuracy in motion analysis.

Original Abstract Submitted

in one embodiment, a method includes receiving an input video comprising a plurality of image frames including an object of interest. based on the plurality of image frames, a motion associated with the object of interest is determined, and the plurality of image frames are classified using a machine-learning model to identify one of the plurality of image frames that indicates a moment of perception of the determined motion.