Research Article
Study on the Automatic Basketball Shooting System Based on the Background Subtraction Method
Table 2
Methods used to update background models.
| Method name | Description | Characteristics |
| Median | Median value between continuous multiple-frame sequences as the grayscale value of pixel in fixed time scales | Inconveniently obtains time sequence | Mean | As to the “median” method but the average value of frame sequence as the pixel value | Sensitive to light variation in the environment and dynamic background | Kalman filter | Predicts image transform results on the basis of Kalman filter theory | Long time to eliminate noise and uncontrollable procedure process | Single Gauss | Takes each grayscale value of pixel as the stochastic variable, and the whole process follows Gauss distribution | Convenient calculation process, but bad performance in a complicated scenario | Multiple Gauss | Superimposes a single Gauss process, multimodal situation in a complicated scenario | More model to superimpose and complies with a complicated scenario | Nuclear density | A nonparameter method estimates the current pixel value in a certain moment using nuclear density function | Prior distribution is not needed to know before calculating the density function of the sample |
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