嘗試進行Kinect2.0相機進行標定

1. Color鏡頭標定

 $(u_{rgb},v_{rgb},1)=W_{rgb}*(x,y,z)$

Calibration results after optimization (with uncertainties):

Focal Length:          fc = [ 1094.03583   1087.37528 ] +/- [ 55.02816   51.42175 ]
Principal point:       cc = [ 942.00992   530.35240 ] +/- [ 13.00131   31.27892 ]
Skew:             alpha_c 
 
= [ 0.00000 ] +/- [ 0.00000  ]   => angle of pixel axes = 90.00000 +/- 0.00000 degrees
Distortion:            kc = [ 0.06857   -0.10542   0.00233   0.00092  0.00000 ] +/- [ 0.02206   0.02884   0.00379   0.00492  0.00000 ]
Pixel error:          err = [ 0.49343   0.67737 ]

2. 紅外鏡頭標定

 $(u_{ir},v_{ir},1)=W_{ir}*(x,y,z)$

Calibration results after optimization (with uncertainties):

Focal Length:          fc 
 
= [ 379.40726   378.54472 ] +/- [ 40.73354   34.75290 ]
Principal point:       cc = [ 263.73696   201.72450 ] +/- [ 9.17740   30.29723 ]
Skew:             alpha_c = [ 0.00000 ] +/- [ 0.00000  ]   => angle of pixel axes = 90.00000 +/- 0.00000 degrees
Distortion:            kc = [ 0.03377   -0.04195   0.00519   0.00734  0.00000 ] +/- [ 0.07368   0.25678   0.01111   0.00965  0.00000 
 
]
Pixel error:          err = [ 0.88997   0.92779 ]

根據上面兩個式子可以推匯出兩個影象畫素之間的對應關係。先將RGB影象對映和depth同樣大小。

3. 2個相機相對關係計算

 前面兩個相機都是以相機中心作為世界座標系的原點。要建立兩個相機之間的關係，需要構建以統一的世界座標系。以深度相機中心為世界座標的原點。

則RGB相機和相機原點存在如下關係

$(x_{w},y_{w},z_{w})=(x_{ir},y_{ir},z_{ir})=R*(x_{rgb},y_{rgb},z_{rgb})+T$

補充：兩個相機的配準問題當前的好多部落格裡寫的方法，根據color和Ir 的外參計算的說法很扯淡。

因為2個影象的解析度不同，外參根本不在一個框架下。這應該是一個立體匹配的問題。

A Quantitative Comparison of Calibration Methods for RGB-D Sensors Using Different Technologies
https://github.com/rgbdemo/rgbdemo/blob/master/calibration/calibrate_kinect.cpp

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