A 3D database of everyday objects for vision research
A 3D database of everyday objects for vision research
复制标题
用于视觉研究的日常物体 3D 数据库
DOI：
10.1167/16.12.289
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发表时间：
2016
影响因子：
1.8
通讯作者：
Hibbard P
中科院分区：
文献类型：
--
作者：
Hibbard P
对自然图像统计的研究帮助我们理解了视觉系统编码和处理信息的方式。就深度和距离而言，现有的一些数据库可以在自然场景中评估这些统计数据。这些数据库倾向于关注包含相对较远的对象的场景。我们已经开发了一个数据库的3D模型的个别对象，并结合这些方法，创建场景中，这些对象分布在近空间。这种方法补充了现有的数据集，并允许我们评估可达距离内的对象的深度统计。该范围对于理解人类双眼深度感知特别相关。我们使用激光扫描仪和彩色相机创建日常物品的3D模型。然后，我们使用OpenGL计算机渲染场景，其中这些对象被随机放置在模拟观察者面前的虚拟桌面上。我们使用这种方法来创建具有相应的地面真实距离数据的双目图像对。这种方法有许多优点。首先，它避免了对视觉和深度信息进行共配准的需要，并消除了相机位置的不确定性。其次，它允许重要变量的参数变化，如相机间的分离，景深和照明条件。第三，它允许创建多模态刺激，因为对象可以在视觉和触觉上呈现。这种控制水平对于统计分析和心理物理实验的刺激的产生都是有用的。
The study of natural image statistics has helped us to understand the way that the visual system encodes and processes information. In the case of depth and distance, a number of databases exist that allow these statistics to be assessed in natural scenes. These databases tend to focus on scenes containing relatively distant objects. We have developed a database of 3D models of individual objects, and a method for combining these, to create scenes in which these objects are distributed in near space. This approach complements existing datasets, and allows us to assess depth statistics for objects within reachable distance. This range is particularly relevant for understanding human binocular depth perception. We created 3D models of everyday objects using a laser scanner and colour camera. We then computer-rendered scenes, using OpenGL, in which these objects were randomly positioned on a virtual table top in front of the modelled observer. We used this approach to create binocular image pairs with corresponding ground truth distance data. This method has a number of advantages. Firstly, it avoids the need to co-register visual and depth information, and eliminates uncertainty about the locations of the cameras. Secondly, it allows the parametric variation of important variables such as the inter-camera separation, depth of field and lighting conditions. Thirdly, it allows the creation of multimodal stimuli, since the objects can be rendered both visually and haptically. This level of control is useful for both statistical analysis and the creation of stimuli for psychophysical experiments.