1. A method of training an image recognition tool for detecting images of a person: scanning a first frame in a video stream comprising a sequence of frames for images of a person; generatinq a representation of the region of interest of the first frame likely to contain the image of the person; forming a video track comprising the representation of a region of interest of the first frame likely to contain an image of the person; scanning each subsequent frame in the sequence of frames for images of the person in each subsequent frame, wherein the scanning each frame begins at a location in each frame based on a location of the region of interest of a preceding frame; for each subsequent frame in the sequence of frames: generating a representation of the region of interest of the subsequent frame likely to contain the image of the person; adding, to the video track, the representation of a region of interest of subsequent frame likely to contain the image of the person; assigning a positive label to the video track when the representation of the region of interest in at least one of the first frame and the subsequent frames contains the person and no other people, the positive label identifying the video track as corresponding to the person; and designating each representation of the region of interest in the positively labeled video track as a positive instance and providing each representation of the region of interest in the positively labeled video track to the image recognition tool for training a multiple-instance learning algorithm of the image recognition tool.