1. A computer-implemented method for tracking one or more objects at each position in an interval in a video input with the use of a Kalman filter having a noisy measurement component and a noisy predictor component, comprising: obtaining a first location estimate of an object in the video input at each position in the interval, wherein the first location estimate represents the noisy measurement component of the Kalman filter; obtaining a second location estimate and a movement estimate of the object in the video input at each position in the interval, wherein the second location estimate and movement estimate represent the noisy predictor component of the Kalman filter; and determining a final estimate of at least one selected from the group consisting of (1) a location of the object at a future interval at each position in the interval with the Kalman filter and (2) a velocity of the object at a future interval at each position in the interval with the Kalman filter, wherein each final estimate is determined with reference to a Kalman gain, the Kalman gain indicating a first level of importance of the noisy measurement component and a second level of importance of the noisy predictor component.