SVO學習日記 2 2021 1 16

#include

#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
namespace svo
//析構函式，主要作用是刪除幀上的特徵點  
frame::
~frame()
);}//初始化幀
void frame::
initframe
(const cv::mat& img));
//建立影象金字塔
frame_utils::
createimgpyramid
(img,
max(config::
npyrlevels()
,config::
kltmaxlevel()
+1),img_pyr_);}
//設定關鍵幀
void frame::
setkeyframe()
//向影象上新增特徵點ftr
void frame::
addfeature
(feature* ftr)
//刪除沒有3d點的特徵
void frame::
setkeypoints()
);}//挑選並檢查這些點
void frame::
checkkeypoints
(feature* ftr)
//右上角的點
if(ftr -
> px[0]
>= cu && ftr -
> px[1]
< cv)
//左上角的點
if(ftr -
> px[0]
< cu && ftr -
> px[1]
< cv)
//左下角的點
if(ftr -
> px[0]
< cu && ftr -
> px[1]
>= cv)
}//刪除一些指定的特徵點
void frame::
removekeypoint
(feature* ftr)})
;if(found)
setkeypoints()
;}//判斷是否可見，存在於相機裡
bool frame::
isvisible
(const vector3d& xyz_w)
const
namespace frame_utils
}//獲得場景深度，傳入，幀，深度均值，深度最小值
bool
getscenedepth
(const frame& frame,
double
& depth_mean,
double
& depth_min)}if
(depth_vec.
empty()
)//獲得深度的均值
depth_mean = vk::
getmedian
(depth_vec)
;return
true;}
}}

SVO學習日記 8 2021 2 1

ifndef svo pose optimizer h define svo pose optimizer h include namespace svo endif include include include include include include include namespace ...

SVO學習日記 13 2021 2 22

include include include include include include include include include include include include include include include include include include includ...

SVO學習日記 14 2021 2 23

做了兩件事 1.通過影象對齊,計算乙個粗糙的位姿 2.建立乙個當前幀的區域性地圖,根據地圖對比位姿進一步優化 二.影象對齊 1.目的 迭代計算幀間位姿 解釋 用於影象對齊的地圖點是上一幀能看到的地圖點,我們知道影象幀間變換比較小,有理由相信上一幀所看到的場景大部分相同 過程 1 找到前一幀看到的地圖...