daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Simple grammar correction from context

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I do with computer vision -> I work on computer vision

The author may have also meant "I can do this with computer vision"
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Pavel Savchenko 2016-07-07 13:36:57 +02:00 committed by GitHub
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00-Preface.ipynb
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@ -328,7 +328,7 @@
"\n",
"Sensors are noisy. The world is full of data and events that we want to measure and track, but we cannot rely on sensors to give us perfect information. The GPS in my car reports altitude. Each time I pass the same point in the road it reports a slightly different altitude. My kitchen scale gives me different readings if I weigh the same object twice.\n",
"\n",
"In simple cases the solution is obvious. If my scale gives slightly different readings I can just take a few readings and average them. Or I can replace it with a more accurate scale. But what do we do when the sensor is very noisy, or the environment makes data collection difficult? We may be trying to track the movement of a low flying aircraft. We may want to create an autopilot for a drone, or ensure that our farm tractor seeded the entire field. I do with computer vision, and I need to track moving objects in images, and the computer vision algorithms create very noisy and unreliable results. \n",
"In simple cases the solution is obvious. If my scale gives slightly different readings I can just take a few readings and average them. Or I can replace it with a more accurate scale. But what do we do when the sensor is very noisy, or the environment makes data collection difficult? We may be trying to track the movement of a low flying aircraft. We may want to create an autopilot for a drone, or ensure that our farm tractor seeded the entire field. I work on computer vision, and I need to track moving objects in images, and the computer vision algorithms create very noisy and unreliable results. \n",
"\n",
"This book teaches you how to solve these sorts of filtering problems. I use many different algorithms, but they are all based on *Bayesian probability*. In simple terms Bayesian probability determines what is likely to be true based on past information. \n",
"\n",