1. A computer-implemented method comprising: tracking position of at least one object in a plurality of video frames, the tracking comprising: processing an initial frame of a set of frames of the plurality of video frames, the processing the initial frame using feature extraction to identify locations, in the initial frame, of features of the at least one object; using motion estimation to track locations of the features in subsequent frames of the set of frames, comprising iteratively performing: obtaining a next frame of the set of frames; and applying a motion estimation algorithm as between the next frame and a prior frame of the set of frames to identify updated locations of the features in the next frame, wherein locations of the features as identified based on the prior frame are used as input to the motion estimation algorithm to identify the updated locations of the features in the next frame based on searching less than an entirety of the next frame; recognizing occurrence of an event, halting the iteratively performing based on recognizing the occurrence of the event, the halting defining the end of the set of frames; and based on recognizing the occurrence of the event and the halting the iteratively performing, repeating, for each additional set of one or more subsequent sets of frames of the plurality of video frames, the processing an initial frame and the using motion estimation to track locations of the features, wherein the processing the initial frame of a respective additional set uses feature extraction to identify locations, in the initial frame of the additional set, of the features, and the using motion estimation to track locations of the features in subsequent frames of the additional set comprises iteratively performing the obtaining a next frame and the applying the motion detection algorithm as between the next frame and a prior frame of the additional set of frames.