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Reconstructing Shape and Texture of 3D Object by Active Wearable Vision Sensor

利用主动可穿戴视觉传感器重建 3D 物体的形状和纹理

基本信息

批准号：
14380161
负责人：
SUGIMOTO Akihiro
金额：
$ 9.66万
依托单位：
National Institute of Informatics
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2002
资助国家：
日本
起止时间：
2002 至 2004
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-14380161/
关键词：
wearable vision sensor shape reconstruction surface reflectance 3D image registration motion estimation computer vision wearable vision 装着型視角センサ視線情報ウェアラブルビジョン

项目摘要

To establish man-machine interactions in the wearable computer environments, we studied reconstructing the shape and texture of a 3D object that a user takes in his hands through the active wearable vision sensor information. Obtained research results can be summarized as follows.1.Detecting blink points of a person using active wearable vision sensor.We developed a wearable vision sensor that consists of the detector of person's viewing lines and two active cameras. First, we established a method for calibrating the sensor so that it can detect person's blink points accurately even in a real situation such that the depth of blink points changes. Next, we proposed a method for detecting a gazing region of a person.2.Shape reconstruction of a hand-held 3D object.We proposed a registration method for range images that preserves local structures of object surfaces. The method introduces shape patterns and a skewness of correspondences, both of which are extracted from the local surface ne … More arby a point of interest in each image. These two features enable us to reconstruct full shape of a 3D object that preserves local structures of object surfaces.3.Reflectance estimation of a 3D object under complex illumination.We developed a method for recovering reflectance properties of a moving Lambertian object from an image sequence of the object taken by a fixed camera under unknown and complex illumination. Our method enables us to synthesize realistic images of the object in arbitrary poses under arbitrary lighting conditions by using the reconstructed shape and albedo.4.Ego-motion estimation using active wearable vision sensor.We proposed a method for incrementally estimating ego motion by two mounted active cameras. Our method independently controls the two cameras during the ego motion so that each camera automatically fixates its optical axisto its own fixation point. Two cameras do not have to share the common field of view in this case whereas in stereo vision they have to do. Less

为了在可穿戴计算机环境中建立人机交互，我们研究了通过主动可穿戴视觉传感器信息重建用户手中的3D对象的形状和纹理。取得的研究成果可以概括如下：1.主动式可穿戴视觉传感器检测人的眨眼点我们研制了一种可穿戴视觉传感器，该传感器由人的视线检测器和两个主动式摄像机组成。首先，我们建立了一种校准传感器的方法，使其能够准确地检测人的眨眼点，即使在真实的情况下，眨眼点的深度变化。其次，提出了一种检测人的注视区域的方法。2.手持三维物体的形状重建提出了一种保持物体表面局部结构的距离图像配准方法。该方法引入了形状模式和对应的偏斜度，这两者都是从局部表面NE中提取的。 ...更多信息通过在每个图像中的感兴趣的点。这两个特征使我们能够重建完整的三维物体的形状，保持物体表面的局部结构。3.复杂光照下的三维物体的反射率估计我们提出了一种方法，用于从未知和复杂光照下的固定相机拍摄的物体的图像序列中恢复运动朗伯物体的反射率特性。我们的方法使我们能够合成真实的图像，在任意姿态和任意照明条件下，通过使用重建的形状和姿态。4.自我运动估计的主动可穿戴视觉传感器。我们提出了一种方法，增量估计自我运动由两个安装主动摄像机。我们的方法在自我运动期间独立地控制两个摄像机，使得每个摄像机自动地将其光轴固定到其自身的固定点。在这种情况下，两个摄像头不必共享公共视场，而在立体视觉中，它们必须共享公共视场。少