Based on the characteristics of line structured light sensor, a speedy method for the calibration was established. With the coplanar reference target, the spacial pose between camera and optical plane can be calibrate...Based on the characteristics of line structured light sensor, a speedy method for the calibration was established. With the coplanar reference target, the spacial pose between camera and optical plane can be calibrated by using of the camera’s projective center and the light’s information in the camera’s image surface. Without striction to the movement of the coplanar reference target and assistant adjustment equipment, this calibration method can be implemented. This method has been used and decreased the cost of calibration equipment, simplified the calibration procedure, improved calibration efficiency. Using experiment, the sensor can attain relative accuracy about 0.5%, which indicates the rationality and effectivity of this method.展开更多
This paper theoretically analyzes and researches the coordinate frames of a 3D vision scanning system, establishes the mathematic model of a system scanning process, derives the relationship between the general non-or...This paper theoretically analyzes and researches the coordinate frames of a 3D vision scanning system, establishes the mathematic model of a system scanning process, derives the relationship between the general non-orthonormal sensor coordinate system and the machine coordinate system and the coordinate transformation matrix of the extrinsic calibration for the system.展开更多
Egocentric recognition is exciting computer vision research by acquiring images and video from the first-person overview.However,an image becomes noisy and dark under low illumination conditions,making subsequent hand...Egocentric recognition is exciting computer vision research by acquiring images and video from the first-person overview.However,an image becomes noisy and dark under low illumination conditions,making subsequent hand detection tasks difficult.Thus,image enhancement is necessary to make buried detail more visible.This article addresses the challenge of egocentric hand grasp recognition in low light conditions by utilizing the flex sensor and image enhancement algorithm based on adaptive gamma correction with weighting distribution.Initially,a flex sensor is installed to the thumb for object manipulation.The thumb placement that holds in a different position on the object of each grasp affects the voltage changing of the flex sensor circuit.The average voltages are used to configure the weighting parameter to improve images in the image enhancement stage.Moreover,the contrast and gamma function are used to adjust varies the low light condition.These grasp images are then separated to be training and testing with pretrained deep neural networks as the feature extractor in YOLOv2 detection network for the grasp recognition system.The proposed of using a flex sensor significantly improves the grasp recognition rate in low light conditions.展开更多
文摘Based on the characteristics of line structured light sensor, a speedy method for the calibration was established. With the coplanar reference target, the spacial pose between camera and optical plane can be calibrated by using of the camera’s projective center and the light’s information in the camera’s image surface. Without striction to the movement of the coplanar reference target and assistant adjustment equipment, this calibration method can be implemented. This method has been used and decreased the cost of calibration equipment, simplified the calibration procedure, improved calibration efficiency. Using experiment, the sensor can attain relative accuracy about 0.5%, which indicates the rationality and effectivity of this method.
文摘This paper theoretically analyzes and researches the coordinate frames of a 3D vision scanning system, establishes the mathematic model of a system scanning process, derives the relationship between the general non-orthonormal sensor coordinate system and the machine coordinate system and the coordinate transformation matrix of the extrinsic calibration for the system.
基金This research is supported by the NationalResearch Council of Thailand(NRCT).NRISS No.144276 and 2589488.
文摘Egocentric recognition is exciting computer vision research by acquiring images and video from the first-person overview.However,an image becomes noisy and dark under low illumination conditions,making subsequent hand detection tasks difficult.Thus,image enhancement is necessary to make buried detail more visible.This article addresses the challenge of egocentric hand grasp recognition in low light conditions by utilizing the flex sensor and image enhancement algorithm based on adaptive gamma correction with weighting distribution.Initially,a flex sensor is installed to the thumb for object manipulation.The thumb placement that holds in a different position on the object of each grasp affects the voltage changing of the flex sensor circuit.The average voltages are used to configure the weighting parameter to improve images in the image enhancement stage.Moreover,the contrast and gamma function are used to adjust varies the low light condition.These grasp images are then separated to be training and testing with pretrained deep neural networks as the feature extractor in YOLOv2 detection network for the grasp recognition system.The proposed of using a flex sensor significantly improves the grasp recognition rate in low light conditions.
