CAJ | 학술논문

刚性目标轮廓具有明显几何特性且不易受光照、纹理和颜色等因素影响。结合上述特性和图像稀疏表示原理,提出一种适用于刚性目标的分级检测算法。在基于部件模型(Part-based model, PBM)的框架下,采用匹配追踪算法将目标轮廓自适应地稀疏表示为几何部件的组合,根据部件与目标轮廓的匹配度,构建描述部件空间关系的有序链式结构。利用该链式结构的有序特性逐级缩小待检测范围,以匹配度为权值对各级部件显著图进行加权融合生成目标显著图。 PASCAL 图像库上的检测结果表明,该检测方法对具有显著轮廓特征的刚性目标有较好的检测结果,检测时耗较现有算法减少约60%～90%。
강성목표륜곽구유명현궤하특성차불역수광조、문리화안색등인소영향。결합상술특성화도상희소표시원리,제출일충괄용우강성목표적분급검측산법。재기우부건모형(Part-based model, PBM)적광가하,채용필배추종산법장목표륜곽자괄응지희소표시위궤하부건적조합,근거부건여목표륜곽적필배도,구건묘술부건공간관계적유서련식결구。이용해련식결구적유서특성축급축소대검측범위,이필배도위권치대각급부건현저도진행가권융합생성목표현저도。 PASCAL 도상고상적검측결과표명,해검측방법대구유현저륜곽특정적강성목표유교호적검측결과,검측시모교현유산법감소약60%～90%。
The profile of rigid ob jects has the geometrical characteristic and is insusceptible to illumination, texture or color. In this paper, a hierarchical detection algorithm for ridge objects based on geometric sparse representation of profile is presented. In the framework of part-based model (PBM), the object profile is automatically divided into geometrical parts by the sparse representation using the matching pursuit algorithm. To describe the spatial relationship of the geometrical parts, an ordered chain-like structure is constructed according to the order of the matching degree of the parts and the ob ject profile. With the ordered chain-like structure, the detection range is gradually shrunk at each hierarchy. The final salient map of the object is the weighted summation of the parts0 salient maps, and the weights are defined as the matching degrees. The simulation on the PASCAL datasets shows that the proposed method outperforms the existing models in rigid objects detection, and saves 60%to 90%detection time compared to the state-of-art methods.