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Spectral technique to recognise occluded objects

机译：识别被遮挡物体的光谱技术

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摘要

When recognising partially visible objects in a scene, a good global decision should be made based on locally gathered features for their recognition, since global information is no longer reliable. This local-to-global nature of occlusion recognition leads us to spectral matching technique. Unfortunately, conventional spectral matching is not desirable for noisy data set from a cluttered scene. In this study, a top-down procedure is introduced into a standard spectral matching for the recognition of occluded objects. Feature points are firstly evaluated and associated with object(s) of interest. Subsequently, geometrical consistency is enforced to find correct correspondences among the candidate matches with high association scores. Based on this two-stage strategy, both appearance and geometric information are taken into consideration. Our algorithm is implemented for both 2D and 3D occluded objects recognition under different occlusion rates. It is shown that the improvement has been made for spectral correspondence algorithm to recognise occluded objects and it has a comparable recognition rate with the state-ofthe- art recognition methods.
机译：识别场景中部分可见的对象时，应基于本地收集的特征来做出良好的全局决策以对其进行识别，因为全局信息不再可靠。遮挡识别的这种局部到全局的性质使我们找到了光谱匹配技术。不幸的是，对于来自混乱场景的嘈杂数据集，常规频谱匹配是不可取的。在这项研究中，自顶向下的过程被引入到标准光谱匹配中以识别被遮挡的物体。首先评估特征点并将其与感兴趣的对象相关联。随后，强制执行几何一致性，以在关联得分较高的候选匹配中找到正确的对应关系。基于此两阶段策略，同时考虑了外观和几何信息。我们的算法适用于在不同遮挡率下的2D和3D遮挡物体识别。结果表明，光谱对应算法在识别被遮挡物体方面已经取得了进步，并且其识别率与最新的识别方法相当。

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