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Read on to find out more about the highest and lowest paying jobs in America, and discover what makes a job fun.S. How much can you make doing fun jobs? What makes a job fun anyway? Highest and Lowest Paying Jobs in the U.S. Surgeons might save lives and be among the highest paid Americans, but that doesn’t mean morale is high. If you think the jobs that pay the most are also the most fun, perhaps you should talk to someone in one of those professions. You might find the opposite is true. Take a look at a 2014 list of the median salaries for some of the highest paying jobs in the U.S. Beyond fat paychecks, the thing many of these professions have in common is general job dissatisfaction. The majority of these positions require a secondary degree, and some also involve extensive internships or residencies. You would think that amusement park workers would be having at least some fun.|Python is a popular programming language used for web and software development. If you're just getting started programming computers and other devices, chances are you've been trying to figure out which programming language is the best to learn first. There are many articles on the internet about what programming language you should be learning - which are the best for what platform, which are easiest to learn, which are the most likely to help you land a job making the big money. If you've been sifting through all those opinions, chances are good you've heard of Python. There probably isn't a single right answer to your question. Learning any programming language will also teach you how to think like a programmer. All programming languages have their strengths and weaknesses. If you're looking for a language that works in a broad range of applications, or just want to dip your toe into the coding waters, Python may be good to try. Potential applications of such kind of trajectory analysis tool could be intelligent review systems that would enhance the training activities, but also richer broadcasting contents that would increase the engagement of spectators. The drawback of these approaches is that they require the careful and time-consuming installation of the sensor devices on the athlete and the acquisition of a precise ground model. Furthermore, such an approach could be not always achievable during competitions. Computer vision techniques applied on videos capturing the athlete’s performance is a valid option to obtain trajectories without the need of sensor networks nor ground surface models. The benefit of a video-based approach is even more evident considering the usual practice of video reviewing during training or the amount of video material produced by the broadcasting of competitions. However, to the best of our knowledge, no study is currently present to reconstruct the trajectory of skiing athletes in videos. In this short paper, we present a prototype to achieve the reconstruction of the trajectory of skiers in videos acquired from uncalibrated and unconstrained cameras. bbc sports

















































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