What is the optical flow?
Optical flow describes computer tracking of moving objects by analyzing the content differences between video recordings. In the video, the object and the observer can be in motion; The computer can find stimuli that indicate the boundaries, edges and areas of individual static images. Detection of their procedures allows the computer to monitor the object in time and space. This technology is used in industries and research, including the operation of unmanned air vehicles (UAVs) and safety systems. Optical flow -based flow measures changes in image and time. Scan the dense plane of the flow field. Film -based function based on the overlap of objects within the object indicates progress.
This technique resembles the camera image stabilization, allowing the calculated field to be locked into the frame and via the shivers of the camera. Calculate the algorithms of the optical tokushod between the pictures in the sequence. The computer divides each image into a square grid. Overlap two pictures allows comparison to find the best square matchesat. When the computer finds a match, it draws the boundary between the difference, sometimes called needles.
algorithms systematically work from coarse to fine resolution. This allows you to monitor movement between images with differences in resolution. The computer does not recognize objects, but only detects and follows those characteristics of objects that can be compared between images.
Optical flow calculation vectors can detect and monitor objects as well as extract the dominant plane of the image. This can help with robotic navigation and visual odometry or orientation and position of the robot. It remarks not only objects, but also the surrounding environment in three dimensions and gives robots more viable spatial consciousness. Calculated vectors in plane allows the processor to deduce and respond to movements extracted from the frames.
Some weaknesses of optical flow technology include data loss that is the result of squares that computer cannot match the limiti pictures. These unbeatable areas remain unoccupied and create planar cavities, which reduces accuracy. Clean edges or stable elements such as corners contribute to the flow analysis.
Detailed factors may be covered if the observer is also in motion, because it cannot distinguish certain elements from frame to frame. The analysis divides movement into an apparent global flow and a localized movement of the object or Egomotion. Spatial changes in the edges or the intensity of the image are lost in the movement of the camera and the global flow of the movable environment. The analysis is improved if the computer can eliminate the effect of a global flow.