- #Kinovea video analysis how to#
- #Kinovea video analysis pdf#
- #Kinovea video analysis full#
- #Kinovea video analysis Pc#
Here are some topics that could be covered: It should be useful for evaluating new hardware on the market and as a buyers guide.
#Kinovea video analysis pdf#
Maybe at some point we can create a PDF or something. Please add your input, illustrative images, comments, remarks, additional degrading factors, formatting suggestions, etc. We are now very near a day where little USB cameras can be considered serious imaging devices. The trigger for this topic though, is the advent of high-quality, interchangeable, small lenses for surveillance-type cameras. This list should be general and relevant to anything that can provide a stream of image and store it on-device or transmit it to a computer (DSLR, Industrial camera, USB camera, IP camera, Smartphone, etc.). Just as for the start-up speed, the data analysis can also be used for other parameters.I would like to use this thread to compile a list of quality-degrading factors in video, how much they are relevant to sport analysis, which component are involved, and how we may improve upon them.
#Kinovea video analysis Pc#
The data is now in the cache of your PC and you can paste it with STR+V e.g. This can be done by right clicking on the graph and then choose “Copy Data to Clipboard”. If you want to further process the data with another program, you can of course export the data. After clicking on “Add Curves”, the curves appear in the graph for all the digitized frames. From this we want the speed in X and in Y direction. In this case, we do not select a segment, but the athlete’s centre of gravity (CG). Now another window opens, in which you specify which curves the program should show you. We want to examine the run-up velocity of the athlete and therefore choose: Linear > Kinematics > Add Position, Velocity and Acceleration Do you want to analyze linear or angular data? Do you want the program to display kinematic or kinetic parameters? With a right click on the newly created analysis window you can choose between various options and select the one that best fits your needs. SkillSpector also offers a wide range of options for this: Window > New Analysis Window
These are needed, for example, to determine the center of gravity of the body or to calculate energy curves. As already described in the main article, the underlying body model, which we defined in step 2, calculates the weights of the individual segments using certain percentages of the total body mass.
In our case we recorded with 100fps, so the time between two frames is 0.01s. To enable the complete data analysis we have to enter two more values: The first is the frame rate, because the program needs the exact time between two frames to later determine the speeds and the derivatives of them (as you know: v = s / t). To check and visualize the calibration, the digitized sequence can be viewed in an animation at this point: Window > New Animation Video Now you have to go back to the movement environment: Digitizing > Mode > Movement We think this a cool feature, which definitely helps to save time. After you have labeled the first frame, the cursor automatically jumps to the position where it expects the corresponding marker in the next frame. This depends on your model and is shown in the bottom right corner of the program (blue arrow). Here you have to select the anatomical landmarks by hand in the given order. This model consists of 15 single body segments, which are labeled with a total of 18 marker points.Īs calibration method we choose “Default 2D”.ĭigitization of the movement: Digitizing > Mode > Movement
#Kinovea video analysis full#
In this case we chose the “Simple Full Body”. SkillSpector already has some built-in biomechanical models that can be used. Select model and calibration method: Sequence > Model Wizard > Simple Full Body > Default 2D We have proceeded as follows: Create a new sequence and load the video to be analyzed: Digitizing > Open Video
#Kinovea video analysis how to#
We are going to explain how to use SkillSpector using the athlete’s run-up velocity as an example (we have taken more parameters, but more on this later).
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