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This paper proposes a method for detecting moving objects appeared in video captured by a moving camera. The proposed method relies on dense optical flow to differentiate moving objects from static background. Whenever video taken from a static camera is used, the dense optical flow itself is sufficient to determine the moving object in the scenes. However, in a non-static camera, all pixels are moving...
Spatio-temporal differentiation method is one of the most effective methods of determining the velocity of moving objects owing to its low calculation cost, unnecessity of feature points. It is expected that the method can be used in real world. However, it is difficult to estimate optical flow in real time, because it must wait for 3 frames of image that the spatio-temporal differentiation method...
Optical flow is referred to as velocity distribution of object image, and we have used spatio-temporal differentiation method to obtain optical flow. It is possible to obtain optical flow fast by the method, but the high velocity may induce large systematic errors. So, we introduced the compensation method for reducing the magnitude of velocity which is applied to spatio-temporal differentiation....
In this paper, we are suggested the best tracking algorithm for mobile robot fusing both image and distance information. Proposed tracking algorithm is a kind of improved CAMSHIFT algorithm combined with SURF, Optical Flow and Ultra-Sonic data, to enhance the tracking capability. Since CAMSHIFT algorithm is based HSV color space model, it is vulnerable to the lighting, brightness and speed of the...
In this research, a method for dense 3D reconstruction of structures from small motion of a spherical camera is proposed. Spherical cameras can capture information from all directions enabling measurement of the entire surrounding structure at once. The proposed technique uses two spherical images clicked at slightly displaced positions near the structure, followed by a combination of feature-point...
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