Collaborative Display Overlay Prediction for Low-Latency Input

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Solution Overview

Problem

Collaborative content projection systems experience undesirable latency due to continuous data flow between the display, receiver, and the device storing the original file, leading to delays in displaying user inputs on the projected image.

Innovation Solution

A method involving a receiver that generates an overlay image based on user input data, which is displayed before updating the original image, reducing latency by predicting the user input's extended portion using spatial or time coordinates, machine learning, or neural networks, and determining the input type.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the original file is stored on the teacher's desktop and processed through multiple devices (display, receiver, desktop), then the collaborative content projection system can function, but latency increases due to continuous data flow between devices

Engineering Contradiction:
Improvecollaborative content projection system functionalityVSAvoidlatency
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The receiver generates an overlay image based on user input data before receiving the updated real image from the desktop. This preliminary action allows the overlay image to be displayed immediately, reducing the perceived latency while the actual file processing continues in the background on the desktop device.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The overlay image acts as an intermediary visual element between the user input and the updated real image. It provides a temporary visual representation of user actions during the data transmission and processing delay, making the system response appear more responsive without compromising the reliability of the complete data flow.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Loss of time

If the receiver generates and displays an overlay image based on user input data, then latency is reduced, but the system complexity increases

Engineering Contradiction:
ImprovelatencyVSAvoidsystem complexity
Core Design Contradiction:
Loss of timeVSDevice complexity

Solution Approach 1:

The visual output is segmented into two separate components: the real image (original content) and the overlay image (user input representation). This segmentation allows the receiver to process and display the overlay image independently and immediately, reducing latency, while maintaining the integrity of the original file processing workflow on the desktop.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The receiver changes the visual parameters of the displayed image by superimposing the overlay image on top of the real image. This parameter change (adding a visual layer) provides immediate feedback to users without requiring changes to the underlying file processing parameters or system architecture.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP4066509B1Methods and systems for reducing latency on a collaborative platform
Publication Date: 2025.12.31 SCREENBEAM INC
  • EP4066509B1 patent drawingFigure 1A
  • EP4066509B1 patent drawingFigure 1B
  • EP4066509B1 patent drawingFigure 2

AI summary

Systems and methods for reducing latency on a collaborative platform are provided. The collaborative platform involves a display, a moderator device, one or more member devices, and a receiver in communication with the display, the moderator device, and the one or more member devices. To reduce latency of the collaborative platform, the receiver generates an overlay image based on user input received from the display, as well as user type of the user input, generates an overlaid image based on the overlay image, and transmits the overlaid image for display, while a collaboration application generates new real image(s) based on the user input for display. The overlaid image generated may be indicative of actual user input as well as predicted user input using extrapolation and/or machine learning.