In some cases, the size of the images is so small that can hardly represent a real-life scene. In any case, the problem is computationally very complex, so most of the proposed solutions are based on strong simplifications adapted to the technology available at the time or to the specific applications they intend to solve. However, in many occasions, the optical flow allows obtaining valid approximations of the movement being actually recorded.ĭetermining optical flow is a subject that has been studied by means of computers for several decades, and it has been employed in applications, such as (a) three-dimensional image segmentation, (b) support for navigation of autonomous robots or, in general, the detection of obstacles to avoid collisions, (c) synchronization and/or ‘matching’ of video scenes, and (d) fluid dynamics analysis. Since most applications rarely meet the aforementioned conditions, it is considered that the method is approximate and that it does not allow the reconstruction of the original movement produced in the three-dimensional scene. These are, as described by Beauchemin and Barron, (a) uniform illumination, (b) surfaces with Lambertian reflectance, and (c) movement limited to the plane of the image. Technically, optical flow computation is based on assumptions rarely observed in real cases, but they can be partially met and so be considered as valid approximations. In fact, it is not possible to determine whether a velocity vector is obtained due to an actual motion of an object or a movement of the camera that has captured the image or a variation of luminosity due to some environmental condition such as reflections or shadows. Moreover, optical flow computation techniques are based on analyzing the brightness variations of each pixel, making it impossible to distinguish between true and apparent motion. The movement represented by the optical flow is considered an apparent movement since, in fact, the set of vectors generated is obtained from a two-dimensional image arising from projecting the real image (three-dimensional) on the plane of the camera. However, the apparent simplicity by which the human eye interprets movement in a three-dimensional space represents a highly complex task when trying to emulate it with computers - even in the case of a single motion. To determine the apparent motion of objects in an image, the information generated by the optical flow and by a separate process that identifies the different objects can be used. For each image of the sequence, it generates a vector at each image pixel representing the apparent motion in the corresponding sampling period. Therefore, the optical flow works on an image sequence. The detection can be performed in real time while images are being captured, or afterwards, when they are already stored in video format. Optical flow is an image analysis technique used to detect motion in video sequences.
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