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This paper describes a fully automated framework to generate realistic head motion, eye gaze, and eyelid motion simultaneously based on live (or recorded) speech input. Its central idea is to learn separate yet interrelated statistical models for each component (head motion, gaze, or eyelid motion) from a prerecorded facial motion data set: 1) Gaussian(More)
In recent years, more and more transistors have been integrated within the GPU, which has resulted in steadily rising power consumption requirements. In this paper we present a preliminary scheme to statistically analyze and model the power consumption of a mainstream GPU (NVidia GeForce 8800gt) by exploiting the innate coupling among power consumption(More)
In recent years, data-driven speech animation approaches have achieved significant successes in terms of animation quality. However, how to automatically evaluate the realism of novel synthesized speech animations has been an important yet unsolved research problem. In this paper, we propose a novel statistical model (called SAQP) to automatically predict(More)
Most of current facial animation editing techniques are frame-based approaches (i.e., manually edit one keyframe every several frames), which is ineffective, time-consuming, and prone to editing inconsistency. In this paper, we present a novel facial editing style learning framework that is able to learn a constraint-based Gaussian Process model from a(More)
Most of current facial animation approaches largely focus on the accuracy or efficiency of their algorithms, or how to optimally utilize pre-collected facial motion data. However, human perception, the ultimate measuring stick of the visual fidelity of synthetic facial animations, was not effectively exploited in these approaches. In this paper, we present(More)
Lifelike interface agents (e.g. talking avatars) have been increasingly used in human-computer interaction applications. In this work, we quantitatively analyze how human perception is affected by audio-head motion characteristics of talking avatars. Specifically, we quantify the correlation between perceptual user ratings (obtained via user study) and(More)
Modern GPUs have been rapidly and increasingly used as a powerful engine for a variety of general-purpose computing applications due to their enormous parallelism and throughput capabilities. However, GPU power consumption still remains high since more and more transistors are integrated into its chip. Until now, how to increase and optimize energy(More)
This paper describes a preliminary study of characterizing performance and power consumption characterization of 3D mobile games. We choose Quake3 and XRace as the game benchmarks and study them on TI OMAP3430, Qualcomm Snapdragon S2, and NVIDIA Tegra 2 (three mainstream mobile System-on-Chip architectures) by selectively disabling different graphics(More)