Code (see comments for more detailed descriptions):

batchProcessRemoteFlash.m 
	Reads in raw photon counts data and outputs histogram statistics such as estimated peak bin, pulse width, and two-bounce energy, as
 	well as binary shadow classification.  Output saved as "params.mat"
processRawCounts.m
	Reads in .csv that contains individual photon count and marker pulse information and generates a datacube in which counts are 
	binned by timing bin and pixel position.
datacubeStats.m
	Reads in dataCube and computes signal statistics for each histogram such as estimated peak bin, pulse width, and two-bounce energy, 
	as well as binary shadow classification
computesDepthsAndAlbedos.m
	Generates range and albedo maps of scene, and also combines range map with galvo scan angle information to save a point cloud 
	representation of scene.  Input is "params.mat".  Output is "results.mat".
twoBounceDetectionProbabilities.m
	Generates gated two-bounce images, map of expected two-bounce energies based on scattering point position and albedo, and assuming 
	no shadow.  Map of probabilities that each pixel contains a two-bounce signal (i.e. it isn't in shadow).  Input is "results.mat", 
	output saved as "two_bounce_detections.mat"
bounceFlashRobustCarvingScript.m     
	Performs shadow based space carving based reconstruction.  Input is generated by twoBounceDectionProbabilities.m.  Script uses
	a number of functions saved in IBO_ECCV folder              
Data_Collection
	Folder that contians code used to run experiments, collect data, and convert raw data to readable formats.  Included here to help
	clarify various inputs that are used in range and depth estimation scripts (for instance, arrays of galvo pointing directions).                           
IBO_ECCV
	A number of subfunctions used in bounceFlashRobustCarvingScript.m which were taken from a previous work published by the author:
		C. Henley, T. Maeda, T. Swedish, and R. Raskar, “Imaging behind occluders using two-bounce light,” 
		in Computer Vision – ECCV 2020. Cham: Springer International Publishing, 2020, pp. 573–588.	                          
          
Data:

TCI_large_scene_16pts:  Data collection described in Section IV-A, Range and Reflectance Imaging in a Room-Like Setting.  And also IV-C-2, 
	Recovering the Geometry of Back-Facing Surfaces.
TCI_large_scene_4pts: Data used to produce Figure 5.            
Depth_Chart_Collection: Data collection described in Section IV-B, Validation of Geometry Estimates.                                    
IBO_Collection: Data collection described in Section IV-C-3, Recovering the Shape of Hidden Objects
Replica_Collection_and_Bias_Lookup_Table: See Appendix B-A, Correcting for a Bias Introduced by a Finite Fitting Window