Time-of-Flight Cameras: Principles, Methods and Applications (SpringerBriefs in Computer Science)

Time-of-flight (TOF) cameras provide a depth value at each pixel, from which the 3D structure of the scene can be estimated. This new type of active sensor makes it possible to go beyond traditional 2D image processing, directly to depth-based and 3D scene processing. Many computer vision and graphics applications can benefit from TOF data, including 3D reconstruction, activity and gesture recognition, motion capture and face detection. It is already possible to use multiple TOF cameras, in order to increase the scene coverage, and to combine the depth data with images from several colour cameras. Mixed TOF and colour systems can be used for computational photography, including full 3D scene modelling, as well as for illumination and depth-of-field manipulations. This work is a technical introduction to TOF sensors, from architectural and design issues, to selected image processing and computer vision methods.

TOF（Time-of-flight）相機在每個像素提供深度值，從中可以估計場景的3D結構。這種新型主動式感測器使得可以直接進行基於深度和3D場景的處理，超越了傳統的2D圖像處理。許多計算機視覺和圖形應用可以從TOF數據中受益，包括3D重建、活動和手勢識別、動作捕捉和人臉檢測。已經可以使用多個TOF相機來增加場景覆蓋範圍，並將深度數據與多個彩色相機的圖像結合。混合TOF和彩色系統可用於計算攝影，包括完整的3D場景建模，以及照明和景深操作。本書從架構和設計問題到選擇的圖像處理和計算機視覺方法，是對TOF感測器的技術介紹。