Face models from noisy 3D cameras
Face models from noisy 3D cameras
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来自嘈杂的 3D 相机的面部模型
DOI：
10.1145/1899950.1899962
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Curio C
中科院分区：
文献类型：
--
作者：
Breidt M;Bülthoff HH;Curio C
负担得起的3D视觉即将进入消费产品的大众市场，如视频游戏机或电视机。在这种情况下拥有深度信息有利于分割以及获得对光照效果的鲁棒性，这两者在处理典型客厅情况下的彩色摄像机数据时都是困难的问题。有几种技术从实时立体、飞行时间(TOF)或实时结构光等相机数据计算3D(或更确切地说是2.5D)深度信息，但都会在相当低的分辨率下产生噪声深度数据。不足为奇的是，目前大多数应用程序仅限于使用全身的基本手势识别。特别是，TOF相机对于紧凑、简单和快速的2.5D深度测量来说是一种相对较新和有前途的技术。由于测量红外光从被摄体反弹时的飞行时间的测量原理，这些设备的图像分辨率相对较低(176 x 144...320 x 240像素)，原始数据中存在高水平的噪声。
Affordable 3D vision is just about to enter the mass market for consumer products such as video game consoles or TV sets. Having depth information in this context is beneficial for segmentation as well as gaining robustness against illumination effects, both of which are hard problems when dealing with color camera data in typical living room situations. Several techniques compute 3D (or rather 2.5D) depth information from camera data such as realtime stereo, time-of-flight (TOF), or real-time structured light, but all produce noisy depth data at fairly low resolutions. Not surprisingly, most applications are currently limited to basic gesture recognition using the full body. In particular, TOF cameras are a relatively new and promising technology for compact, simple and fast 2.5D depth measurements. Due to the measurement principle of measuring the flight time of infrared light as it bounces off the subject, these devices have comparatively low image resolution (176 x 144 ... 320 x 240 pixels) with a high level of noise present in the raw data.
面部动画的语义 3D 运动重定向
DOI：
10.1145/1140491.1140508
发表时间：
2006
期刊：
影响因子：
--
作者：
Curio C;Breidt M;Kleiner M;Vuong QC;Giese MA;Bülthoff HH
通讯作者：
Bülthoff HH