IEEE Trans Pattern Anal Mach Intell. 2011 Aug;33(8):1489-501. doi: 10.1109/TPAMI.2010.224. Epub 2010 Dec 23.
CENsus TRansform hISTogram (CENTRIST), a new visual descriptor for recognizing topological places or scene categories, is introduced in this paper. We show that place and scene recognition, especially for indoor environments, require its visual descriptor to possess properties that are different from other vision domains (e.g., object recognition). CENTRIST satisfies these properties and suits the place and scene recognition task. It is a holistic representation and has strong generalizability for category recognition. CENTRIST mainly encodes the structural properties within an image and suppresses detailed textural information. Our experiments demonstrate that CENTRIST outperforms the current state of the art in several place and scene recognition data sets, compared with other descriptors such as SIFT and Gist. Besides, it is easy to implement and evaluates extremely fast.
本文引入了一种新的视觉描述符 CENsus TRansform hISTogram (CENTRIST)，用于识别拓扑位置或场景类别。我们表明，位置和场景识别，特别是对于室内环境，需要其视觉描述符具有与其他视觉领域（例如，对象识别）不同的属性。CENTRIST 满足这些属性，适合位置和场景识别任务。它是一种整体表示，具有很强的类别识别通用性。CENTRIST 主要编码图像内的结构属性，并抑制详细的纹理信息。我们的实验表明，与其他描述符（如 SIFT 和 Gist）相比，CENTRIST 在几个位置和场景识别数据集上的表现优于当前的最先进水平。此外，它易于实现，评估速度极快。
