基于不动点方程解析求解的高动态场景多尺度分割

项目名称： 基于不动点方程解析求解的高动态场景多尺度分割

项目编号： No.61461022

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 张印辉

作者单位： 昆明理工大学

项目金额： 45万元

中文摘要： 探索高动态场景图像多尺度建模策略与尺度间耦合机制实现可靠分割是图像处理领域的一大挑战，其关键是低尺度局部线索相似性与高尺度整体特征统一性耦合以及算法求解准确性。现有方法通常在缺乏整体位置约束且搜索空间较大的原图像域寻找目标整体特征，耦合后验与真实分布一致性也无法保证。本项目提出在维度较低的小波近似系数空间检测目标并施加整体位置约束，用不动点方程解析求解提高耦合准确性。研究高尺度近似系数内目标整体轮廓检测及位置映射，耦合低尺度色彩和纹理相似性局部特征。研究后验与真实分布信息投影变分下界凸对偶及其不动点方程解析求解并确定信度传播策略，准确推理多尺度后验分布。用高动态场景标准库和机器人视觉计算平台获取高动态图像开展分割实验，与SWA、MNC、gPb多尺度分割算法进行性能对比。本项目旨在探索整体与局部特征多尺度耦合机制，解决耦合后验与真实分布不一致难题，为动态场景下准确推理和鲁棒分割提供理论依据。

中文关键词： 图像分割；区域分割；边缘检测；边缘分割

英文摘要： Exploring multiscale modeling strategy and interscale coupling mechanism of highly dynamic scenes to achieve reliable segmentation remains to be a big challenge for image processing. The key is to couple uniformity of high-scale features with similarity of low-scale cues as well as accuracy of the algorithm. Existing methods usually lack position constraints of overall target features detected in large space of original images and the consistency between coupling posteriori with true distribution can not be guaranteed. We propose to detect targets in the lower dimensional wavelet approximation coefficients to apply overal position constraints and improve coupling accuracy via analytical solution of fixed-point equation. We plan to investigate target contour detection and position mapping methods in high-scale approximation coefficients so as to couple low-scale color and texture similarity in local features. To investigate belief propagation strategy for exact inference of posterior distribution by obtaining analytical solution of fixed-point equation of the convex dual, which is derived from variational lower bound of information projection between posterior and real distribution. Carrying out segmentation experiments on highly dynamic scene benchmarks as well as images acquired by robot vision platform and compare with SWA, MNC and gPb algorithms. The scientific objective is to explore coupling mechanism of overall and local features as well as address non-consistency between posterior inference and real distribution to achieve exact inference of highly dynamic scenes for the purpose of robust segmentation.

英文关键词： Image segmentation;regional segmentation;boundary detection;boundary segmentation