Optical Flow Meter---Part 2
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Optical Flow Meter---Part 2 Algorithms work systematically from coarse to fine resolutions. This permits motion tracking 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 frames. Computing optical flow meter vectors can detect and track objects and also extract an image's dominant plane. This can aid in robotic navigation and visual odometry, or robot orientation and position. It notes not only objects but also surrounding environs in three dimensions, and gives robots more lifelike spatial awareness. Vectors computed in a plane allow the processor to infer and respond to movements extracted from the frames. Some weaknesses of the optical flow meter technique include data loss that results from squares the computer cannot match between images. These unmatched areas remain vacant and create planar voids, reducing accuracy. Clear edges or stable elements like corners contribute to flow analysis. Detailed factors may be obscured if the observer is also in motion, since it can't distinguish certain elements from frame to frame. The analysis divides motion into apparent global flow and localized object motion, or ego motion. Spatial-temporal changes in edges or image intensity get lost in the motion of the camera and the global flow of the moving environment. Analysis is enhanced if the computer can eliminate the effect of the global flow. |
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