运动感知的移动游戏帧率调整算法  

Motion-aware Frame Rate Adjustment Algorithm for Mobile Game

作　　者：梁宇智 霍宇驰 王锐[1] LIANG Yu-Zhi;HUO Yu-Chi;WANG Rui(State Key Lab of Computer Aided Design and Computer Graphics(Zhejiang University),Hangzhou 310058,China)

机构地区：[1]计算机辅助设计与图形学国家重点实验室(浙江大学),浙江杭州310058

出　　处：《软件学报》2025年第2期874-885,共12页Journal of Software

基　　金：国家自然科学基金(61906090,U20B2064,61773208);江苏省自然科学基金(BK20191287,BK20170809);中央高校基本科研业务费专项资金(30920021131);中国博士后科学基金(2018M632304)。

摘　　要：随着移动设备的广泛普及,其图形处理器的性能也逐渐增强.为了满足用户对卓越体验的不断追求,移动设备屏幕分辨率和刷新率每年都在不断提升.与此同时,移动游戏中的可编程绘制流水线也变得日益复杂,这导致游戏应用成为移动设备功耗的主要来源.研究了移动游戏中的绘制流水线,提出一种运动感知的绘制帧率调整方法,以在节能模式下保证绘制质量.与以往仅考虑历史帧绘制误差的预测模型不同,该方法通过建立摄像机位姿和帧间绘制误差的非线性关系模型,通过未来帧新的摄像机位姿预测其绘制误差,实现更为精确的帧率调整策略.此外,该方法还包括一个轻量级的场景识别模块,可根据玩家所处特定场景有针对性地调整误差阈值,从而采用不同程度的帧率调整策略.在定量对比上,相比只考虑历史帧误差的预测模型,构建的模型在游戏帧序列上的预测准确性提高30%以上.同时,在用户实验的定性对比上,相同跳帧比例下该方法能够得到用户体验更好的绘制效果.提出的算法融合了历史帧误差和摄像机位姿变化信息,能够预测出更准确的未来帧误差.算法结合预测结果和场景识别结果,实现了更好的动态帧率调整效果.As mobile devices are widely used,the performance of their graphics processors has increasingly improved.To meet users’continuous pursuit of excellent experience,the screen resolution and refresh rate of mobile devices are constantly increasing every year.At the same time,the programmable shading pipeline in mobile games is becoming more complex,which leads to game applications becoming the main source of power consumption for mobile devices.This work studies the rendering pipeline in mobile games and proposes a motion-aware rendering frame rate adjustment method to ensure rendering quality in power-saving mode.Unlike previous prediction models that only consider rendering errors of historical frames,this method builds a nonlinear model between camera pose and inter-frame rendering error and predicts error based on the new frame’s camera pose,thus achieving more accurate frame rate adjustment strategies.In addition,the method also includes a lightweight scene recognition module that can adjust the error threshold according to the specific scene where the player is located,thereby adopting different degrees of frame rate adjustment strategies.Quantitatively compared with the prediction model that only considers historical frame errors,the proposed model improves the prediction accuracy on game frame sequences by more than 30%.At the same time,in the qualitative comparison of user experiments,under the same frame-skipping ratio,the proposed algorithm can achieve higher rendering quality and better user experience.The algorithm integrates historical frame errors and camera information to predict more accurate future frame errors.It also combines prediction and scene recognition results to achieve better dynamic frame rate adjustment performance.

关 键 词：实时绘制 能耗优化 自适应帧率调整 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]