of further information, such as projection of light patterns onto the scene. Hence,all information must be taken from standard 2D images.The most prominent, and the most detailed in this book, isShape from stereo disparity, where the same scene is imaged from two distinct (displaced) viewpoints and the difference (disparity) between pixel positions (one from each image) corresponding to the same scene point is exploited雙目立體視覺；主動主要爲結構光的和激光雷達（lidar），它們原理不同但又有同爲主動式的相同之處。結構光的常用在近距離，高精度的。lidar用在遠的。
2 被動和主動相比：(P15)In contrast, as long as the surface is not too dark (low reflectivity) or specular, and does not have too many deep concavities (‘missing parts’), active stereo systems allow comprehensive shape measurements and give good renderings for multi-viewpoint visualizations. Thus, when the density of features is low, or the resolution of image sensing is low compared to the scale of the imaged texture, an active stereo system is the preferred solution. However, the need to scan a laser spot or stripe or to project a structured light pattern brings with it extra complexity and expense, and potential eye-safety issues.
3 高分辨率的相機發展，人臉識別方面在應用（q:當然也能辨別出散股，翹股等狀態）(P15)A good example is the human face where the random pattern of facial pores can be extracted and hence used to solve the correspondence problem in a passive system.
4 3d成像和形態分析的12里程碑：
no.12 A！ 實時人體姿態識別：看P23的F1.11圖，From a single depth image, range pixels can be labeled as belonging to certain body parts, which are colored differently in the figure. From this labeling,
3D joint positions can be inferred.深度圖像-》身體部分-》3D關節提案 Kinect-XBox即應用此技術 To achieve high frame rates, extremely simple
and computationally cheap 3D features were employed based on depth comparisons and randomized decision forest classifiers were trained and implemented to run on
a GPU.(P24) 機器學習
no.11 A！ 3D形狀匹配：熱核簽名 因爲問題for One problem with spin images and other local shape descriptors is that they are encoded in Euclidean space and are only valid for rigid local shapes.效果如圖F1.10很清楚。
no.10 AA！ 被動3D成像：靈活的相機標定 Many current approaches to camera calibration are based on the easy-to-use, yet accurate approach presented by Zhang in 2000, the motion between the captures is not required, hence the system is easy to use