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-# Summary
-
-In this report we analysed how distance metrics learning affects classification
-accuracy for the dataset CUHK03. The baseline method used for classification is
-Nearest Neighbors based on Euclidean distance. The improved approach we propose 
-mixes Jaccardian and Mahalanobis metrics to obtain a ranklist that takes into 
-account also the reciprocal neighbors. This approach is computationally more 
-complex, since the matrices representing distances are effectively calculated 
-twice. However it is possible to observe a significant accuracy improvement of 
-around 10% for the $@rank1$ case. Accuracy improves overall, especially for
-$@rankn$ cases with low n.
+
+# Forulation of the Addresssed Machine Learning Problem
+
+## Probelm Definition
 
 The person re-identification problem presented in this paper requires mtatching 
-pedestrian images from disjoint camera's by pedestrian detectors. This problem 
-is challenging, as identities captured in photsos are subject to various 
-lighting, pose, blur, background and oclusion from various camera views. This 
-report considers features extracted from the CUHK03 dataset, following a 50 layer 
-Residual network (Resnet50). This paper considers distance metrics techniques which 
-can be used to perform person re-identification across **disjoint* cameras, using 
-these features.
-
-## CUHK03
+pedestrian images from disjoint camera's by pedestrian detectors. This problem is 
+challenging, as identities captured in photsos are subject to various lighting, pose, 
+blur, background and oclusion from various camera views. This report considers 
+features extracted from the CUHK03 dataset, following a 50 layer Residual network 
+(Resnet50). This paper considers distance metrics techniques which can be used to 
+perform person re-identification across **disjoint* cameras, using these features.
+
+## Dataset - CUHK03  Summary
 
 The dataset CUHK03 contains 14096 pictures of people captured from two 
 different cameras. The feature vectors used, extracted from a trained ResNet50 model