研究目的
To investigate the implementation and design issues for augmented reality applications on mobile platforms, focusing on parameters such as trigger response time and battery consumption, and their dependence on trigger image complexity, 3D object complexity, and ambient light.
研究成果
The research concludes that trigger response time (TRT) decreases with more trigger feature points but can increase at extreme ambient light levels. Battery consumption increases with higher 3D mesh complexity. Designers must balance detail in AR experiences with performance and battery life considerations. Ambient light also affects TRT and should be accounted for in application design. Future work should extend these findings to other platforms and further investigate parameter dependencies.
研究不足
The study is limited to a single mobile device (One Plus 3T) and Android OS; results may not generalize to other platforms or operating systems. The experiments assume no other applications are running, which may not reflect real-world usage. Future work could explore these parameters across various devices and OS, and investigate the effects of high-frequency points in trigger images.
1：Experimental Design and Method Selection:
The experiment was designed to measure the impact of various parameters on trigger response time (TRT) and battery consumption in an AR application. The application was developed using Vuforia for image recognition, Unity for app development and rendering, and Blender for 3D object design. TRT was measured from camera API call to trigger recognition API call, and battery consumption was measured using Android APIs.
2：Sample Selection and Data Sources:
The mobile platform used was a One Plus 3T Android phone. 3D objects with varying mesh complexities and trigger images with different feature points were designed and tested. Ambient light was varied using a potentiometer-based lighting system with a standard white LED.
3：List of Experimental Equipment and Materials:
One Plus 3T smartphone, lux meter for ambient light measurement, Vuforia platform, Unity platform, Blender software, and a lighting system with potentiometer and LED.
4：Experimental Procedures and Operational Workflow:
The AR application was developed by designing trigger images, creating 3D objects in Blender, integrating with Vuforia for image tracking, and coding in Unity. Experiments involved varying trigger image complexity (number of feature points), 3D mesh size, and ambient light intensity, then measuring TRT and battery consumption under controlled conditions (WiFi and data off, screen brightness at 50%).
5：Data Analysis Methods:
Data on TRT and battery consumption were collected and analyzed to observe trends and impacts of the varied parameters, with results presented graphically.
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