deletions | additions       diff --git a/section_Introduction_The_use_of__.tex b/section_Introduction_The_use_of__.tex  index 177128f..3203509 100644  --- a/section_Introduction_The_use_of__.tex  +++ b/section_Introduction_The_use_of__.tex 
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While the performance of video sensors for more simple traffic variables has been more extensively studied, not all factors have been systematically analyzed and the issues with parameter optimization and the lack of separate calibration and validation datasets are widespread. Besides, the relationship of tracking performance with performance for traffic parameters has never been investigated.   The objective of this paper is first to improve the performance of existing automated detection and tracking methods for video data in terms of the  accuracy of tracking, but also of  different kinds of traffic data such as counts, speeds, gaps and road user interactions. This is done through the optimization of tracking parameters using a genetic algorithm comparing the tracker output with manually annotated trajectories. The method is applied to a set of traffic videos extracted from a large surrogate safety study of roundabout merging zones~\cite{st-aubin15big-data}, covering factors such as the distance of road users to the camera, two types of cameras, the camera resolution and two weather conditions. The second objective is to explore the transferability of parameters for separate datasets with the same properties (consecutive video samples) and across different properties, by reporting how optimizing tracking for one condition impacts performance in terms of tracking and traffic parameters for the other conditions. This paper is a follow up on \cite{ettehadieh15systematic} that investigates more factors and how tracking performance is related to the accuracy of traffic parameters. This paper is organized as follows: it provides in the next section a brief overview of the current state of computer vision and calibration in traffic applications, then presents the detailed methodology including the ground truth inventory, measures of performance and calibration procedure, followed by a presentation and discussion of the results to conclude with a summary and recommendations for future research.   
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