系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2013年
4期
1050~1057
,共null页
李乐 张茂军 程钢 熊志辉
李樂 張茂軍 程鋼 熊誌輝
리악 장무군 정강 웅지휘
建筑物面 特征线段累积 特征优化 动态规划
建築物麵 特徵線段纍積 特徵優化 動態規劃
건축물면 특정선단루적 특정우화 동태규화
building facet; feature line segment accumulation; feature refined; dynamic programming
将建筑物划分为单个的建筑物面进行处理可以有效降低街景图像理解的复杂度.因此,文中提出一种基于建筑物特征线段累积的动态规划方法用于检测街景图像中各个建筑物面的信息.该方法结合系统工程分析问题的方法,根据图像建筑物区域直线特征丰富的特点,分析不同朝向类型的建筑物面中水平直线段透视投影后的变化,建立相应的特征累积数学模型量化建筑物区域蕴含的直线段特征,并给出相应的算法优化平滑特征线段累积结果,最后证明了根据特征线段累积结果识别建筑物面的过程符合动态规划最优性原理,通过动态规划的方法求解识别目标区域内所包含的各类建筑物面.实验证明,该文的方法可以准确的识别街景图像中各类建筑物面,而且算法复杂度更低,处理速度更快.
將建築物劃分為單箇的建築物麵進行處理可以有效降低街景圖像理解的複雜度.因此,文中提齣一種基于建築物特徵線段纍積的動態規劃方法用于檢測街景圖像中各箇建築物麵的信息.該方法結閤繫統工程分析問題的方法,根據圖像建築物區域直線特徵豐富的特點,分析不同朝嚮類型的建築物麵中水平直線段透視投影後的變化,建立相應的特徵纍積數學模型量化建築物區域蘊含的直線段特徵,併給齣相應的算法優化平滑特徵線段纍積結果,最後證明瞭根據特徵線段纍積結果識彆建築物麵的過程符閤動態規劃最優性原理,通過動態規劃的方法求解識彆目標區域內所包含的各類建築物麵.實驗證明,該文的方法可以準確的識彆街景圖像中各類建築物麵,而且算法複雜度更低,處理速度更快.
장건축물화분위단개적건축물면진행처리가이유효강저가경도상리해적복잡도.인차,문중제출일충기우건축물특정선단루적적동태규화방법용우검측가경도상중각개건축물면적신식.해방법결합계통공정분석문제적방법,근거도상건축물구역직선특정봉부적특점,분석불동조향류형적건축물면중수평직선단투시투영후적변화,건립상응적특정루적수학모형양화건축물구역온함적직선단특정,병급출상응적산법우화평활특정선단루적결과,최후증명료근거특정선단루적결과식별건축물면적과정부합동태규화최우성원리,통과동태규화적방법구해식별목표구역내소포함적각류건축물면.실험증명,해문적방법가이준학적식별가경도상중각류건축물면,이차산법복잡도경저,처리속도경쾌.
It would be more easily to process the image of street scene by recognizing every building facet first. In this paper, a novelty method which recognizes every building facet by analyzing feature line segment of buildings with technique of system engineering is proposed. Beginning, the feature line segments extracted from the area of buildings are accumulated with the mathematics' model which deduced by the relation of horizontal lines between the real world and image. Then the result of feature accumulation is refined by a new method. At last, each building facet could be recognized by dynamic programming because the building facet recognition by analyzing feature line segments has been proved to comply with the optimality principle. The experiment shows that our method could recognize building facet exactly in many complex environments and need less time in the fields of building facet recognition.