cost function

distance & tracking cost

easy... just [g-p+view_vector]^2 + (r-r_d)^2

visibility cost

objective: stay way from occluded region in binary matrix

method1

finding maximum box around current azimuth and elevation pros: easy to formulate, just distance from the center of box => optimization good and stable
cons: 1. finding box in binary matrix ... very inflexible? 2. box approximation to unoccluded region ...

method2

signed distance transform -> interpolation or B-spline surface B-spline:https://en.wikipedia.org/wiki/B-spline

pros: 1. no approximation needed. can exploit cast result as it is. 2. B-spline can be a constraint function ... so better to study. cons: optimization on piece wise? B spline curve

hard constraint

B-spline surface

tutorial on B-spline curve

Ch2 http://www.uio.no/studier/emner/matnat/ifi/INF-MAT5340/v05/undervisningsmateriale/kap2-new.pdf

B spline surface practical

http://www.cgl.uwaterloo.ca/ecdfourq/courses/cs779/project.html

B spline tool box

https://github.com/lasote/multivariate-splines

toolbox guide

https://github.com/bgrimstad/splinter/blob/master/docs/cpp_interface.md

if we make install , default install goes to /usr/local/include for headers and /usr/local/lib for lib files. so link "splinter-static-3-0" to project