K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In International Conference on Robotics and Automation, p. 178--183, Japan, 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....object, the variance of the object velocity, and the confidence of the shape estimate to compute a suitable focal length. The influence of the velocity variance ensures that the camera does not zoom in too closely if an object s motion varies greatly, in order to safely maintain acquisition. In [6] the authors use a robot arm and camera zoom to achieve a desired image feature configuration. The focus of the work is on integrating the zoom into the control as a redundant mechanical degree of freedom, as the authors assume that the image Jacobian and thus the 3D positions of the image ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In Proc. of IEEE International Conference on Robotics and Automation, Nagoya, Japan, May 1995, pp. 178--183.

....an object. Furthermore, these degeneracies cannot be detected from a single viewpoint. Wilkes et al. choose a focal length that reduces the probability of view degeneracies, improving the performance of systems designed to recognize objects from a single arbitrary viewpoint. Hosoda et al. [14] develop an interesting controller for robotic systems, which enhances visual servoing using zoom and a manipulator. Their controller is based on the observation that the vision system and the manipulator have complementary characteristics. Zoom can provide a wide range of image changes, but it ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 178--183, Nagoya, Aichi, Japan, May 1995.

....decrease the focal length of the lens. After detecting the button click event, Servolens focal length is controlled by a serial port (9600 bauds) by constant increase (zoom ) or decrease (zoom ) of 4 mm. In visual servoing, more and more applications include the automatic zoom lens control [3] [7], where the surface of an object must be kept constant in the image. In our case, since the image processing is only founded on the position of the image area gazed by the operator s eye, these techniques cannot be applied. 3 Visual data extraction 3.1 The eye tracker An eye tracker is a device ....

....f (5) where f is the current value of the focal length, and m x , m y the size of an elementary pixel of the CCD matrix. As well known in visual servoing, the convergence, stability and robustness of closed loop control laws are not disturbed if these values are not accurately determined. Using [7], we obtain s = X; Y ) and s d = 0; 0) Since only pan and tilt are controlled, the interaction matrix L T s is given by: L T s = XY Gamma(1 X 2 ) 1 Y 2 GammaX Y (6) In this case, we have W = I 2 and thus C = L T s Gamma1 . The control law (4) can finally be detailed as ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In IEEE Int. Conf. on Robotics and Automation, Nagoya, Japan, May 1995.

....object, the variance of the object velocity, and the confidence of the shape estimate to compute a suitable focal length. The influence of the velocity variance ensures that the camera does not zoom in too closely if an object s motion varies greatly, in order to safely maintain acquisition. In [ Hosoda et al. 1995 ] the authors use a robot arm and camera zoom to achieve a desired image feature configuration. The focus of the work is on integrating the zoom into the control as a redundant mechanical degree of freedom, as the authors assume that the image Jacobian and thus the 3D positions of the image ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In Proc. of IEEE International Conference on Robotics and Automation, Nagoya, Japan, May 1995, pp. 178--183.

....object, the variance of the object velocity, and the confidence of the shape estimate to compute a suitable focal length. The influence of the velocity variance ensures that the camera does not zoom in too closely if an object s motion varies greatly, in order to safely maintain acquisition. In [ Hosoda et al. 1995 ] the authors use a robot arm and camera zoom to achieve a desired image feature configuration. The focus of the work is on integrating the zoom into the control as a redundant mechanical degree of freedom, as the authors assume that the image Jacobian and thus the 3D positions of the image ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In Proc. of IEEE International Conference on Robotics and Automation, Nagoya, Japan, May 1995, pp. 178--183.

....almost of the existing methods with omnidirectional vision system have focused on its optogeometric features to reconstruct 3 D scene structure. In this paper, we introduce an omnidirectional vision system on a mobile robot enhanced by an active zoom mechanism. We implement a zoom servoing [4] by which the target image can be captured at the constant position if it moves on the ground plane. It is realized by controlling focal length of the camera. Due to the active zoom mechanism, the target motion in the radius direction can be canceled, and only circular motions around the image ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 178-183, 1995.

....as a sensory system for a goal defending mobile robot. As a method of behavior acquisition, Q learning is used with a state space consisting of ball and goal images. We introduce an omnidirectional vision system with an active zoom mechanism to accelerate the learning. We implement a zoom servoing [4] by which the target image can be captured at the constant position if the target moves on the ground plane. It is realized by controlling focal length of the camera. Due to the active zoom mechanism, the target motion in the radius direction can be canceled, and only circular motions around the ....

K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 178-183, 1995.

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K. Hosoda, H. Moriyama, and M. Asada. Visual servoing utilizing zoom mechanism. In International Conference on Robotics and Automation, p. 178--183, Japan, 1995.

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