18485266. DETECTION OF MOMENT OF PERCEPTION simplified abstract (Apple Inc.)

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 18485266 titled 'DETECTION OF MOMENT OF PERCEPTION

Simplified Explanation

The patent application describes a method for identifying a moment of perception of motion in a video by analyzing image frames and using a machine-learning model.

• Motion associated with an object of interest is determined from a video comprising multiple image frames.
• A machine-learning model is used to classify the image frames and identify the frame that indicates a moment of perception of the determined motion.

Potential Applications

This technology could be applied in various fields such as surveillance, sports analysis, and video editing.

Problems Solved

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

Benefits

The method can improve video analysis efficiency and accuracy, leading to better understanding and utilization of video content.

Potential Commercial Applications

One potential commercial application of this technology could be in the development of video editing software that automatically identifies key moments in videos for easier editing.

Possible Prior Art

One possible prior art for this technology could be existing video analysis software that uses machine learning for object detection and tracking in videos.

Unanswered Questions

How does the machine-learning model handle complex motions in videos?

The article does not provide details on how the machine-learning model is trained to classify image frames with complex motions.

What is the computational cost of implementing this method on a large scale?

The article does not discuss the computational resources required to analyze and classify image frames in real-time or on a large dataset.

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.