Object pose estimation from stereo images with unknown correspondence is a thoroughly studied problem in the computer vision and robot engineering literatures. Especially, it is important to detect the desirable corre...
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Object pose estimation from stereo images with unknown correspondence is a thoroughly studied problem in the computer vision and robot engineering literatures. Especially, it is important to detect the desirable corresponding points from images for object pose estimation. For this, many approaches have been proposed. Among them, the local feature descriptor, which describe the feature points that are robust to image deformations in an object or image, is one of the most promising approaches that has been applied to the stable feature detection problem successfully. Although any descriptors including the SIFT represent superior performance, these are based on luminance information rather than color information thereby resulting in instability to photometric variations such as shadows, highlights, and illumination changes. Therefore, we propose a novel method which extracts the interest points that are insensitive to both geometric and photometric variations in order to estimate more accurate and desirable object pose. In this method, we use photometric quasi-invariant features based on the dichromatic reflection model in order to achieve photometric invariance, and the SIFT is used for geometric invariance as well. The performance of the proposed method is evaluated with other local descriptors. Experimental results show that our method gives similar performance or outperforms them with respect to various imaging conditions. Finally, we estimate object pose by using the features extracted via the proposed method.
In this paper, a new wearable input device recognizing human hand-motion, a keyglove, is proposed. The glove can resolve the disadvantages of the conventional input devices and can be adapted to the mobile computing e...
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ISBN:
(纸本)0780384636
In this paper, a new wearable input device recognizing human hand-motion, a keyglove, is proposed. The glove can resolve the disadvantages of the conventional input devices and can be adapted to the mobile computing environment The device is applicable as the touch-typing input method for users' easy understanding and improvement of input speed. The hand-motion for touch-typewriting using QWERTY keyboard, which is most widely being used currently, is analyzed. The analyzed results show that the model with 21 DOF can be reduced to one with approximately 14 DOF. The hand-motion capture module using low price sensors is also developed for hand-motion recognition. In general, however, typists using the keyglove system can not exactly determine the key position of desired input letter because the virtual keyboard does not have the physical location of key layouts, and that causes many typewriting errors at a long typewriting time. Therefore, an algorithm is needed to cope with the problem and to reduce typewriting errors due to personal disparities such as hand shapes and typewriting habits. For this reason, the time-variant prediction algorithm is proposed to minimize typewriting errors, and the possibility of the developed keyglove system is also verified.
Parallel-type mechanisms provide many advantages over serial-type mechanisms. However, in case of using parallel structures as a haptic device, it is sometimes hard to ensure the performance of the force reflection du...
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ISBN:
(纸本)0780384636
Parallel-type mechanisms provide many advantages over serial-type mechanisms. However, in case of using parallel structures as a haptic device, it is sometimes hard to ensure the performance of the force reflection due to many singular points existing in workspace. In this paper, we propose a redundantly actuated parallel 3-DOF haptic device, which is singularity-free in the workspace and also has an improved force reflection capability. Using two sets of actuators with different size and different force resolution, we propose several useful load distribution algorithms considering force resolution and torque limit. We confirm the performance of the force reflection capability throughout simulation and experimentation.
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