AR Translation Triggering by Pose Change and Frame Matching
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Solution Overview
Problem
AR translation processes require significant computing resources and often result in translation result display jams due to real-time frame-by-frame translation, affecting user experience.
Innovation Solution
An AR translation processing method that detects pose changes and feature similarities between consecutive frames to determine if text needs to be fully, partially, or not translated, optimizing translation triggers and reducing redundant processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time frame-by-frame translation is performed for each acquired image, then translation results are displayed continuously, but computing resources are consumed excessively and translation efficiency is low
Solution Approach 1:
The patent implements periodic action by using pose change detection to trigger translation processing only when necessary. Instead of continuous frame-by-frame translation, the system periodically checks pose changes and performs translation only when the pose change exceeds a threshold, converting continuous processing into discrete periodic operations that reduce computing resource consumption while maintaining translation efficiency
Solution Approach 2:
The patent applies parameter changes by introducing a pose threshold parameter that controls when translation should be triggered. By monitoring pose parameters (position and orientation changes) and comparing them against a threshold, the system dynamically determines whether translation processing is needed, optimizing the balance between translation efficiency and computing resource usage based on actual scene changes
2Ease of operation
If real-time frame-by-frame translation is performed for each acquired image, then translation results are displayed continuously, but display jams occur affecting user experience
Solution Approach 1:
The patent eliminates display jams by replacing continuous translation with periodic translation triggered by pose changes. The system waits for pose changes exceeding a threshold before initiating translation, creating a rhythm of processing that prevents the system from becoming overwhelmed and causing display jams, thereby improving both user experience and translation efficiency
Solution Approach 2:
The patent implements feedback by using pose detection results to control the translation process. The system continuously monitors pose changes and uses this feedback information to decide when to trigger translation, creating a closed-loop control system that adapts to scene changes and prevents display jams by only processing when necessary
3Reliability
If translation is performed for every frame, then all text is translated, but redundant translation occurs wasting computing resources
Solution Approach 1:
The patent uses parameter changes (pose threshold) to control translation triggering, ensuring translation is performed when scene changes indicate new text may be present while avoiding redundant translation when the scene is stable, thus maintaining translation completeness without wasting computing resources on redundant processing
Solution Approach 2:
The patent applies partial action by performing translation only when pose changes exceed a threshold, rather than translating every frame. This selective approach translates only when necessary (partial action), avoiding excessive translation of unchanged content while maintaining reliability by triggering translation when scene changes suggest new text appears
Data Source
AI summary
Provided are an AR translation processing method and an electronic device, which relate to the technical field of communications. By the method, in a scenario in which an electronic device is used for AR translation, a pose change of the electronic device can be detected in real time, and feature matching can be performed on a plurality of consecutive frames of images acquired by a camera, so that whether to-be-translated text needs to be fully translated or partially translated, or needs not to be translated can be determined based on the pose change of the electronic device and a feature matching result, and therefore a corresponding translation trigger strategy is selected. In this way, repeated translation can be effectively avoided, thereby saving computing resources in the AR translation process and improving the translation efficiency to a particular extent.