IEEE Trans Pattern Anal Mach Intell. 2018 Apr;40(4):931-944. doi: 10.1109/TPAMI.2017.2697849. Epub 2017 Apr 25.
sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is also designed, which significantly reduces both computation time and memory usage. In addition, a new binarization technique based on comparisons inside each descriptor histogram is defined, yielding a more compact, faster, yet robust alternative. Results on an exhaustive comparative experimental evaluation show that the revised sGLOH descriptor incorporating the above ideas and combining them according to task requirements, improves in most cases the state of the art in both image matching and object recognition.
sGLOH（移位 GLOH）是一种基于直方图的关键点描述符，它可以与关键点补丁的多个量化旋转相关联，而无需任何重新计算。这个属性可以用来定义两个描述符向量之间的最佳距离，从而避免计算主要方向。此外，sGLOH 可以通过添加全局约束来拒绝不一致的对应关系，无论是作为先验知识还是基于数据。本文彻底重新考虑了 sGLOH，并在鲁棒性、速度和描述符维度方面对其进行了改进。修改后的 sGLOH 嵌入了更多的量化旋转，从而产生了更多正确的匹配。还设计了一种新的快速匹配方案，大大减少了计算时间和内存使用。此外，还定义了一种新的基于每个描述符直方图内部比较的二值化技术，得到了更紧凑、更快但更鲁棒的替代方案。在详尽的对比实验评估中，结果表明，将上述思想纳入并根据任务要求组合的修改后的 sGLOH 描述符在图像匹配和目标识别方面在大多数情况下都提高了现有技术水平。
