Queued Image Recognition for Low-Latency Cloud Game Interaction
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Solution Overview
Problem
The low computing capability of terminals leads to inefficient image recognition and delays in transmitting portrait recognition results to the cloud, resulting in mismatches between virtual object behaviors and user actions in cloud games.
Innovation Solution
A data processing method where image data is received and stored in a queue for simultaneous recognition and transmission, utilizing a service server with high computing capability to perform image recognition and rendering, and implementing frame skipping to process the latest timestamp data for synchronized display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If image recognition is performed on the terminal with insufficient computing capability, then the terminal can directly process the image data, but the image recognition efficiency is low and transmission delay increases
Solution Approach 1:
The patent introduces a service server as an intermediary between the terminal and the cloud game server. The service server receives image data from the terminal, performs image recognition processing to extract object regions, and then transmits the processed data to the cloud game server. This intermediary approach allows the terminal to offload computationally intensive image recognition tasks while maintaining real-time processing capabilities, thereby improving image recognition efficiency and reducing transmission delay simultaneously.
2Measurement precision
If the terminal transmits the entire image data to the cloud for processing, then comprehensive image analysis can be performed, but the transmission bandwidth consumption increases and transmission delay increases
Solution Approach 1:
The service server extracts only the necessary object regions from the complete image data through image recognition processing. Instead of transmitting the entire image, the system extracts and transmits only the relevant object regions (such as user portraits or specific objects of interest) to the cloud game server. This extraction approach maintains the accuracy of image analysis by focusing on key elements while significantly reducing transmission bandwidth consumption and transmission delay.
3Measurement precision
If the terminal transmits the entire image data to the cloud for processing, then comprehensive image analysis can be performed, but the transmission bandwidth consumption increases
Solution Approach 1:
The service server extracts only the necessary object regions from the complete image data through image recognition processing. Instead of transmitting the entire image, the system extracts and transmits only the relevant object regions (such as user portraits or specific objects of interest) to the cloud game server. This extraction approach maintains the accuracy of image analysis by focusing on key elements while significantly reducing transmission bandwidth consumption and transmission delay.
4Stability of the object's composition
If image recognition processing is performed sequentially on received image data, then processing order is maintained, but the processing efficiency decreases when multiple images are received
Solution Approach 1:
The service server performs preliminary image recognition processing on received image data before transmitting the results to the cloud game server. By conducting image recognition in advance and extracting object regions beforehand, the system prepares the data in a format ready for immediate use by the cloud game server. This preliminary action approach maintains processing order consistency while improving overall processing efficiency, as the computationally intensive image recognition is completed before the game logic needs to access the processed data.
Data Source
AI summary
A data processing method includes: receiving first image data transmitted by a first client, and storing the first image data to a receive queue, the first image data being obtained by the first client during running of a cloud application and includes an object; performing image recognition processing on the first image data in the receive queue, and storing, to the receive queue during image recognition processing of the first image data, second image data obtained and transmitted by the first client, to obtain an updated receive queue; and transmitting, when a first object region containing the object in the first image data is extracted through image recognition processing, first object image data in the first object region to a target cloud application server, and simultaneously performing image recognition processing on the second image data with a latest receiving timestamp in the updated receive queue.