Initial Commit

Run_FeatureMatching.m

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+% Type your dataset path
+Path_to_result = './Results\Result_img';
+
+addpath('./Utils_FeatureMatching');
+
+% Run feature extraction & matching 
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_class_room1_340Lux'));
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_class_room2_401Lux'));     
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_class_room3_320Lux'));
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_class_room4_263Lux'));     
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_common_room1_177Lux'));    
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_common_room2_95Lux'));     
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_lounage1_200Lux'));        
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_meeting_room1_198Lux'));
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_meeting_room3_213Lux'));   
+main_feature_matching_analysis(strcat(Path_to_result,'\indoor_meeting_room2_191Lux'));   
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_bench1_6420Lux'));        
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_bench2_5530Lux'));        
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_bicycle1_14230Lux'));     
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_bicycle2_2680Lux'));      
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car1_15310Lux'));         
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car2_5530Lux'));          
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car3_4080Lux'));          
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car4_5520Lux'));          
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car5_5290Lux'));          
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car6_4539Lux'));          
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_car7_8490Lux')); 
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_scene1_7380Lux'));        
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_scene2_7710Lux'));        
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_weed1_3350Lux'));         
+main_feature_matching_analysis(strcat(Path_to_result,'\outdoor_weed2_3010Lux'));

Run_MetricsEvaluation.m

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+% Type your dataset path
+Path_to_datset = './DataSet_AE';
+
+addpath('./Utils_metric');
+
+% Run Metric Evaluator 
+Eval_Metric(strcat(Path_to_datset,'\indoor_class_room1_340Lux\left'));
+Eval_Metric(strcat(Path_to_datset,'\indoor_class_room2_401Lux\left'));     
+Eval_Metric(strcat(Path_to_datset,'\indoor_class_room3_320Lux\left'));
+Eval_Metric(strcat(Path_to_datset,'\indoor_class_room4_263Lux\left'));     
+Eval_Metric(strcat(Path_to_datset,'\indoor_common_room1_177Lux\left'));    
+Eval_Metric(strcat(Path_to_datset,'\indoor_common_room2_95Lux\left'));     
+Eval_Metric(strcat(Path_to_datset,'\indoor_lounage1_200Lux\left'));        
+Eval_Metric(strcat(Path_to_datset,'\indoor_meeting_room1_198Lux\left'));
+Eval_Metric(strcat(Path_to_datset,'\indoor_meeting_room3_213Lux\left'));   
+Eval_Metric(strcat(Path_to_datset,'\indoor_meeting_room2_191Lux\left'));   
+Eval_Metric(strcat(Path_to_datset,'\outdoor_bench1_6420Lux\left'));        
+Eval_Metric(strcat(Path_to_datset,'\outdoor_bench2_5530Lux\left'));        
+Eval_Metric(strcat(Path_to_datset,'\outdoor_bicycle1_14230Lux\left'));     
+Eval_Metric(strcat(Path_to_datset,'\outdoor_bicycle2_2680Lux\left'));      
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car1_15310Lux\left'));         
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car2_5530Lux\left'));          
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car3_4080Lux\left'));          
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car4_5520Lux\left'));          
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car5_5290Lux\left'));          
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car6_4539Lux\left'));          
+Eval_Metric(strcat(Path_to_datset,'\outdoor_car7_8490Lux\left')); 
+Eval_Metric(strcat(Path_to_datset,'\outdoor_scene1_7380Lux\left'));        
+Eval_Metric(strcat(Path_to_datset,'\outdoor_scene2_7710Lux\left'));        
+Eval_Metric(strcat(Path_to_datset,'\outdoor_weed1_3350Lux\left'));         
+Eval_Metric(strcat(Path_to_datset,'\outdoor_weed2_3010Lux\left'));
+
+% Run hyper paramter tester
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_class_room1_340Lux\left'));
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_class_room2_401Lux\left'));     
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_class_room3_320Lux\left'));
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_class_room4_263Lux\left'));     
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_common_room1_177Lux\left'));    
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_common_room2_95Lux\left'));     
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_lounage1_200Lux\left'));        
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_meeting_room1_198Lux\left'));
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_meeting_room3_213Lux\left'));   
+% Test_HyperParam(strcat(Path_to_datset,'\indoor_meeting_room2_191Lux\left'));   
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_bench1_6420Lux\left'));        
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_bench2_5530Lux\left'));        
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_bicycle1_14230Lux\left'));     
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_bicycle2_2680Lux\left'));      
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car1_15310Lux\left'));         
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car2_5530Lux\left'));          
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car3_4080Lux\left'));          
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car4_5520Lux\left'));          
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car5_5290Lux\left'));          
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car6_4539Lux\left'));          
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_car7_8490Lux\left')); 
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_scene1_7380Lux\left'));        
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_scene2_7710Lux\left'));        
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_weed1_3350Lux\left'));         
+% Test_HyperParam(strcat(Path_to_datset,'\outdoor_weed2_3010Lux\left'));
+
+% Extract result img
+Extract_Result(strcat(Path_to_datset,'\indoor_class_room1_340Lux\left'));
+Extract_Result(strcat(Path_to_datset,'\indoor_class_room2_401Lux\left'));     
+Extract_Result(strcat(Path_to_datset,'\indoor_class_room3_320Lux\left'));
+Extract_Result(strcat(Path_to_datset,'\indoor_class_room4_263Lux\left'));     
+Extract_Result(strcat(Path_to_datset,'\indoor_common_room1_177Lux\left'));    
+Extract_Result(strcat(Path_to_datset,'\indoor_common_room2_95Lux\left'));     
+Extract_Result(strcat(Path_to_datset,'\indoor_lounage1_200Lux\left'));        
+Extract_Result(strcat(Path_to_datset,'\indoor_meeting_room1_198Lux\left'));
+Extract_Result(strcat(Path_to_datset,'\indoor_meeting_room3_213Lux\left'));   
+Extract_Result(strcat(Path_to_datset,'\indoor_meeting_room2_191Lux\left'));   
+Extract_Result(strcat(Path_to_datset,'\outdoor_bench1_6420Lux\left'));        
+Extract_Result(strcat(Path_to_datset,'\outdoor_bench2_5530Lux\left'));        
+Extract_Result(strcat(Path_to_datset,'\outdoor_bicycle1_14230Lux\left'));     
+Extract_Result(strcat(Path_to_datset,'\outdoor_bicycle2_2680Lux\left'));      
+Extract_Result(strcat(Path_to_datset,'\outdoor_car1_15310Lux\left'));         
+Extract_Result(strcat(Path_to_datset,'\outdoor_car2_5530Lux\left'));          
+Extract_Result(strcat(Path_to_datset,'\outdoor_car3_4080Lux\left'));          
+Extract_Result(strcat(Path_to_datset,'\outdoor_car4_5520Lux\left'));          
+Extract_Result(strcat(Path_to_datset,'\outdoor_car5_5290Lux\left'));          
+Extract_Result(strcat(Path_to_datset,'\outdoor_car6_4539Lux\left'));          
+Extract_Result(strcat(Path_to_datset,'\outdoor_car7_8490Lux\left')); 
+Extract_Result(strcat(Path_to_datset,'\outdoor_scene1_7380Lux\left'));        
+Extract_Result(strcat(Path_to_datset,'\outdoor_scene2_7710Lux\left'));        
+Extract_Result(strcat(Path_to_datset,'\outdoor_weed1_3350Lux\left'));         
+Extract_Result(strcat(Path_to_datset,'\outdoor_weed2_3010Lux\left'));

Run_NMbasedControl.m

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+% Type your dataset path
+Path_to_result = './Results\Result_Exp';
+
+addpath('./Utils_control');
+
+% Run Test
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_class_room1_340Lux\workspace_upsampled_result.mat'));
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_class_room2_401Lux\workspace_upsampled_result.mat'));     
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_class_room3_320Lux\workspace_upsampled_result.mat'));
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_class_room4_263Lux\workspace_upsampled_result.mat'));     
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_common_room1_177Lux\workspace_upsampled_result.mat'));    
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_common_room2_95Lux\workspace_upsampled_result.mat'));     
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_lounage1_200Lux\workspace_upsampled_result.mat'));        
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_meeting_room1_198Lux\workspace_upsampled_result.mat'));
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_meeting_room3_213Lux\workspace_upsampled_result.mat'));   
+Test_nelder_mead_AE(strcat(Path_to_result,'\indoor_meeting_room2_191Lux\workspace_upsampled_result.mat'));   
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_bench1_6420Lux\workspace_upsampled_result.mat'));        
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_bench2_5530Lux\workspace_upsampled_result.mat'));        
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_bicycle1_14230Lux\workspace_upsampled_result.mat'));     
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_bicycle2_2680Lux\workspace_upsampled_result.mat'));      
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car1_15310Lux\workspace_upsampled_result.mat'));         
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car2_5530Lux\workspace_upsampled_result.mat'));          
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car3_4080Lux\workspace_upsampled_result.mat'));          
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car4_5520Lux\workspace_upsampled_result.mat'));          
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car5_5290Lux\workspace_upsampled_result.mat'));          
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car6_4539Lux\workspace_upsampled_result.mat'));          
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_car7_8490Lux\workspace_upsampled_result.mat')); 
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_scene1_7380Lux\workspace_upsampled_result.mat'));        
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_scene2_7710Lux\workspace_upsampled_result.mat'));        
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_weed1_3350Lux\workspace_upsampled_result.mat'));         
+Test_nelder_mead_AE(strcat(Path_to_result,'\outdoor_weed2_3010Lux\workspace_upsampled_result.mat'));

Utils_Control/FindClosestPoint.m

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+function x_ = FindClosestPoint(x, Flag_dataset) 
+%% Camera Exposure Control for Robust Robot Vision with Noise-Aware Image Assessment Metric
+%
+% Ukcheol Shin, Jinsun Park, Gyumin Shim, Francois Rameau, and In So Kweon
+%
+% IROS 2019
+%
+% Please feel free to contact if you have any problems.
+% 
+% E-mail : Ukcheol Shin ([email protected] / [email protected])
+%          Robotics and Computer Vision Lab., EE,
+%          KAIST, Republic of Korea
+%
+% Project Page : https://sites.google.com/view/noise-aware-exposure-control
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%  Name   : 
+%    FindClosestPoint.m
+%
+%    Returns the nearest point to the input point based on the interval previously used to upsample the dataset.
+%
+%  Modified:
+%
+%    04 December 2019
+%
+%  Author:
+%
+%    Ukcheol Shin
+%
+%  Parameters:
+%
+%  Input    : x                  -  Input point 
+%             : Flag_dataset   -  flag to select the setttings for each dataset  
+%
+%  output  : x_                 - The point closest to the input point present in the upsampled data set
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+    if ( nargin == 1 )
+      Flag_dataset = 1;
+    end
+
+    if(Flag_dataset == 0) % Outdoor dataset
+        Interval_gain      =  2;
+        Interval_expt      =  150;
+        Limit_gain          =  20;
+        Lower_limit_expt =  100;
+        Upper_limit_expt =  7450;
+    elseif(Flag_dataset == 1) % Indoor dataset
+        Interval_gain      =  1;
+        Interval_expt      =  3000;
+        Limit_gain          =  24;
+        Lower_limit_expt =  4000;
+        Upper_limit_expt =  67000;
+    end
+
+    Gain  = x(1,1);
+    Expt  = x(1,2);
+
+    if(mod(Gain,Interval_gain) >= Interval_gain/2)
+        Gain = Gain - mod(Gain,Interval_gain) + Interval_gain;
+    elseif(mod(Gain,Interval_gain) < Interval_gain/2)
+        Gain = Gain - mod(Gain,Interval_gain);
+    end
+
+    if(mod(Expt,Interval_expt) >= Interval_expt/2)
+        Expt = Expt - mod(Expt,Interval_expt) + Interval_expt + Lower_limit_expt;
+    elseif(mod(Expt,Interval_expt) < Interval_expt/2)
+        Expt = Expt - mod(Expt,Interval_expt) + Lower_limit_expt;
+    end    
+
+    if(Gain > Limit_gain)
+        Gain = Limit_gain;
+    elseif(Gain < 0)
+        Gain = 0;
+    end
+
+    if(Expt > Upper_limit_expt)
+        Expt = Upper_limit_expt;
+    elseif(Expt < Lower_limit_expt)
+        Expt = Lower_limit_expt;
+    end
+
+    x_ = zeros(1,2);
+    x_(1,1) = Gain;
+    x_(1,2) = Expt;
+end

Utils_Control/Metric_our.m

@@ -0,0 +1,91 @@
+function f = Metric_our ( x , Path_UpsampledData)
+%% Camera Exposure Control for Robust Robot Vision with Noise-Aware Image Assessment Metric
+%
+% Ukcheol Shin, Jinsun Park, Gyumin Shim, Francois Rameau, and In So Kweon
+%
+% IROS 2019
+%
+% Please feel free to contact if you have any problems.
+% 
+% E-mail : Ukcheol Shin ([email protected] / [email protected])
+%          Robotics and Computer Vision Lab., EE,
+%          KAIST, Republic of Korea
+%
+% Project Page : https://sites.google.com/view/noise-aware-exposure-control
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%  Name   : 
+%    Metric_our
+%
+%   Returns a value based on the proposed image evaluation method for the input point, 
+%   which value is returned based on the "<dataset_name> _upsample.mat" generated by 
+%   the previous "Metric_Evaluaotr.m" and "Data_Interpolation.m" .
+% 
+%  Modified:
+%
+%    04 December 2019
+%
+%  Author:
+%
+%    Ukcheol Shin
+%
+%  Parameters:
+%
+%  Input    : x   -  input point, the dimension of x is 2x1,
+%                      we assume x(1) component is "gain", x(2) component is "exposure time". 
+%  output  : f_x -  Evaluated value based on our metric
+%                      with given input parameter (gain, exposure time)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+  if ( length ( x ) ~= 2 )
+    error ( 'Error: function expects a two dimensional input\n' );
+  end
+
+   % load upsampled dataset. 
+   % In this code, we use pre-calculated datapoint and evaluated value of each dataset. 
+    persistent Xq Yq Zq Interval_Up_Gain Interval_Up_ExpT result_txt;
+    if ( nargin == 2 )
+        load(Path_UpsampledData,'Xq','Yq','Zq', 'interval_ExpT','interval_dB');
+        Interval_Up_Gain = interval_dB;
+        Interval_Up_ExpT = interval_ExpT;
+        result_txt = strcat(Path_UpsampledData(1:regexp(Path_UpsampledData,'workspace')-1), 'Traj_ExpTGain.txt');
+        fileID = fopen(result_txt,'w');
+        fclose(fileID);
+    else
+        fileID = fopen(result_txt,'a');
+        fprintf(fileID , '%4.5f %4.5f\n' , x(1) , x(2));
+        fclose(fileID);
+    end
+
+    Gain = x(1);
+    Expt = x(2);
+
+    if(mod(Gain, Interval_Up_Gain) >= Interval_Up_Gain/2)
+        Approxi_Gain = Gain - mod(Gain, Interval_Up_Gain) + Interval_Up_Gain;
+    elseif(mod(Gain, Interval_Up_Gain) < Interval_Up_Gain/2)
+        Approxi_Gain = Gain - mod(Gain, Interval_Up_Gain);
+    end
+
+    if(mod(Expt, Interval_Up_ExpT) >= Interval_Up_ExpT/2)
+        Approxi_Expt = Expt - mod(Expt, Interval_Up_ExpT) + Interval_Up_ExpT;
+    elseif(mod(Expt, Interval_Up_ExpT) < Interval_Up_ExpT/2)
+       Approxi_Expt = Expt - mod(Expt, Interval_Up_ExpT);
+    end
+
+    Gain_index = find(abs(Xq(1,:) - Approxi_Gain) < 0.001);
+    ExpT_index = find(abs(Yq(:,1) - Approxi_Expt) < 0.001);
+
+    f =  -Zq(ExpT_index,Gain_index);
+
+    % Exception handler for out of range or nonexistent values.
+    if(isnan(f)) 
+        f = 10^10;  % instead of using "inf", use some large number
+    elseif(isempty(f))
+        f = 10^10;
+    end
+
+      fprintf ( 1, '  %9.3f',  Approxi_Gain );
+      fprintf ( 1, '  %9.3f',  Approxi_Expt );
+      fprintf ( 1, '  %9.3e\n', f );
+
+    return 
+end