camera calibration

基本解釋

The extraction of the internal corners of a planar checkerboard pattern image is a key stage in camera calibration.
基于棋盤格模板圖像內(nèi)部角點的識別是攝像機定標(biāo)過程中的關(guān)鍵環(huán)節(jié)。
The image-based approach may reduce computational delay, eliminate the necessity for image interpretation and eliminate errors due to sensor modeling and camera calibration.
該方法可以減少計算延時，并且對攝像機和機械臂的校準(zhǔn)誤差和目標(biāo)模型誤差具有較強的魯棒性。
This paper introduces a method for camera calibration based on rhombus .
給出了一種基于菱形作為平面模板的攝像機標(biāo)定方法。

相機標(biāo)定
The general principle of camera calibration is studied.
研究了常用的相機標(biāo)定原理。
相機定標(biāo)
So this paper concentrates on the closed form solution for camera calibration.
因此,本文研究了相機定標(biāo)的閉形解。
標(biāo)定技術(shù)
鏡頭標(biāo)定
Traditional multi-camera calibration approaches mainly deal with the static cameras,and which always take advantage of the known camera locations or use calibration tools.
眾所周知,傳統(tǒng)的多目鏡頭標(biāo)定主要針對靜止鏡頭,而且一般是通過事先估計攝像機的架設(shè)位置或者利用標(biāo)定物來計算攝像機之間的關(guān)系,但此類標(biāo)定方法無法直接解決上述問題。
攝影機校準(zhǔn)

標(biāo)定技術(shù)
The intrinsic parameters of camera are found from the feature-point -set of views by means of any one of camera self-calibration techniques. And the traditional camera calibration technique is off-line, however the camera self-calibration technique is on-line.
攝像機自標(biāo)定技術(shù)通過圖像本身的特征求解攝像機內(nèi)參數(shù)，傳統(tǒng)的攝像機標(biāo)定技術(shù)是離線的，而攝像機自標(biāo)定技術(shù)是在線的，因此攝像機自標(biāo)定技術(shù)具有相當(dāng)大的理論價值和實用價值。
相機標(biāo)定
First of all, parallel binocular stereo vision measurement technology is used in this paper. VRML are used to simulate two cameras whose optical axis are parallel, it can simplify the camera calibration and image matching.
首先,本文采用平行雙目立體視覺測量技術(shù),運用VRML模擬兩臺光軸平行的相機,簡化了相機標(biāo)定與圖像匹配。
攝像機標(biāo)定