具有3D空间辨识力的视觉显著计算模型研究

项目名称： 具有3D空间辨识力的视觉显著计算模型研究

项目编号： No.61472380

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 计算机科学学科

项目作者： 曹洋

作者单位： 中国科学技术大学

项目金额： 83万元

中文摘要： 本项目面向3D图像内容，针对现有视觉显著性计算方法的不足，依据目标-场景的3D空间关系，提出具有3D空间辨识力的视觉显著计算模型，并对由此引出的如下科学问题和关键技术开展研究：1）以多尺度图像分割区域作为基元，基于协同优化的思想，融合基于单眼线索和基于立体匹配的深度估计方法，提高自然场景深度估计的精度和鲁棒性。2）利用积木世界模型描述3D场景，通过将图像的各个分割区域模化为带有几何和物理属性的积木实体，基于几何空间约束和物理稳定性约束，采用组合优化策略建立目标与场景间的3D空间关系。3）基于摄影构图的基本规则，寻求从目标-场景的3D空间布局中估计出摄影者想表征的事物或主题，并通过心理学实验获取其视觉显著性的表示方法。4）将3D显著性检测和立体图像分类结合起来，通过设计一个互为上下文关系的迭代框架，采用交替渐进优化的方法，一方面增强显著性区域的3D空间辨识性，另一方面提高图像分类问题的效果。

中文关键词： 显著性；空间辨识力；图像分类；立体匹配；3D场景表示

英文摘要： In this project, a novel discriminative 3D spatial saliency computational model is proposed by using the spatial relations between objects and scene. Most of the state-of-the-art 3D saliency detection methods only take the depth information as the low-level feature, but this ignores the influence of depth information on 3D scene representation. To overcome this, there are four main issues to be addressed in this project: 1). A robust stereo matching algorithm that incorporates the monocular cues contained in the image is presented. The proposed algorithm uses multi-scale image segmented regions as matching primitives and exploits a cooperative optimization procedure to minimize the matching costs of all regions by introducing the cooperative and competitive mechanism between regions. 2). Based on the block world model, a qualitative physical representation of an outdoor scene is presented, where objects have volume and mass, and relationships describe 3D structure and mechanical configurations. Then a novel combinatorial optimization approach is proposed to build up a physically-plausible 3D interpretation of the scene. 3). Inspired by the basic photographic composition rules, a novel saliency computational model is presented, which utilizes the knowledge of photographic composition as priors to express the scenario of photographer. 4）A contextualizing framework, which iteratively and mutually boosts stereo image classification and 3D salient object detection by taking the outputs from one task as the context of the other one, is presented. The proposed solution is supposed to be superior over the existing methods.

英文关键词： Saliency;Discriminative Spatial;Image Classification;Stereo Matching;3D Scence Representation