At present, the synthesizing faces of different ages does not emphasize on feature alignment and rectification of twisted images. If these situations do happen, they might cause failure and inaccuracy on synthesizing images. In this paper, we propose a reversible human facial aging/rejuvenating synthesis system which is implemented by Active Shape Model (ASM) integrated with Log-Gabor Wavelet, which can be used to search for the dementia elderly. First, we use AdaBoost and ASM algorithm to extract the feature set of human face, and rectify them by the concept of facial geometric invariance. The invariant concepts are the distance between inner corners of both eyes and the distance between the nose and chin. Then, we find manually one target image which is similar to the test image from the database, and analyze age texture of this human image by Log-Gabor wavelet in order to retrieve decomposition maps. Finally, we can effectively simulate human facial images of people of different ages by controlling the number of decomposition map of images and objectively judge the results via the density of wrinkles.
In this paper, we present a new mathematical model of three-axis force sensor for underwater robot fingers. We designed a kind of sensor based on this model which has a simple structure and can be miniaturized easily. By this model, they can be calculated that the magnitude, direction of finger force. Moreover, we present a new compensating method to decrease the error caused with the variation of temperature and pressure of water and caused with bending of the beams by symmetrical electronic circuits. We proposed compensation block method to solve the problem of heavy lead wire which affecting finger moving in underwater. Finally, an experiment is performed to verify the proposed model.
This paper proposed a new grasping method for robot fingers with three-axis force sensors. When a robot hand with two fingers is grasping an object, such as an egg, two closed loops with negative feedback in force-control system are start. When grasping force of the two fingers are equal reference force, dynamic balance is reached. Once tiny sliding between egg and finger occurred, force feedback start immediately, dynamic balance is reached again. In this way, our robot hand can firmly grasps eggs, even if vibration added on the robot hand.
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