Depth information is important for autonomous systems to perceive environments and estimate their own state. Traditional depth estimation methods, like structure from motion and stereo vision matching, are built on fe...Depth information is important for autonomous systems to perceive environments and estimate their own state. Traditional depth estimation methods, like structure from motion and stereo vision matching, are built on feature correspondences of multiple viewpoints. Meanwhile, the predicted depth maps are sparse. Inferring depth information from a single image(monocular depth estimation) is an ill-posed problem. With the rapid development of deep neural networks, monocular depth estimation based on deep learning has been widely studied recently and achieved promising performance in accuracy. Meanwhile, dense depth maps are estimated from single images by deep neural networks in an end-to-end manner. In order to improve the accuracy of depth estimation, different kinds of network frameworks, loss functions and training strategies are proposed subsequently. Therefore, we survey the current monocular depth estimation methods based on deep learning in this review. Initially, we conclude several widely used datasets and evaluation indicators in deep learning-based depth estimation. Furthermore, we review some representative existing methods according to different training manners: supervised, unsupervised and semi-supervised. Finally, we discuss the challenges and provide some ideas for future researches in monocular depth estimation.展开更多
Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in th...Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental condi- tions, without using a set of infrared light emitting diodes （LEDs） on the parachute part of the dro- gue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effective- ness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.展开更多
This article proposes a monocular trajectory intersection method,a videometrics measurement with a mature theoretical system to solve the 3D motion parameters of a point target.It determines the target’s motion param...This article proposes a monocular trajectory intersection method,a videometrics measurement with a mature theoretical system to solve the 3D motion parameters of a point target.It determines the target’s motion parameters including its 3D trajectory and velocity by intersecting the parametric trajectory of a motion target and series of sight-rays by which a motion camera observes the target,in contrast with the regular intersection method for 3D measurement by which the sight-rays intersect at one point.The method offers an approach to overcome the technical failure of traditional monocular measurements for the 3D motion of a point target and thus extends the application fields of photogrammetry and computer vision.Wide application is expected in passive observations of motion targets on various mobile beds.展开更多
The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Far...The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Farneback algorithm is used to calculate the optical flow field of the first-view video frames taken by the on-board image transmission camera.Based on the optical flow information,a fuzzy obstacle avoidance controller is then designed to generate the FWAV steering commands.Experimental results show that the proposed obstacle avoidance method can accurately identify obstacles and achieve obstacle avoidance for FWAVs.展开更多
Objective:To explore the changes of lateral geniculate body and visual cortex in monocular strabismus and form deprived amblyopic rat,and visual development plastic stage and visual plasticity in adult rats.Methods:A ...Objective:To explore the changes of lateral geniculate body and visual cortex in monocular strabismus and form deprived amblyopic rat,and visual development plastic stage and visual plasticity in adult rats.Methods:A total of 60 SD rats ages 13 d were randomly divided into A,B,C three groups with 20 in each group,group A was set as the normal control group without any processing,group B was strabismus amblyopic group,using the unilateral extraocular rectus resection to establish the strabismus amblyopia model,group C was monocular form deprivation amblyopia group using unilateral eyelid edge resection+lid suture.At visual developmental early phase(P2S),meta phase(P3S),late phase(P45)and adult phase(P120),the lateral geniculate body and visual cortex area 17 of five rats in each group were exacted for C-fos Immunocytochemistry.Neuron morphological changes in lateral geniculate body and visual cortex was observed,the positive neurons differences of C-fos expression induced by light stimulation was measured in each group,and the condition of radiation development of P120 amblyopic adult rats was observed.Results:In groups B and C,C-fos positive cells were significantly lower than the control group at P25(P<0.05),there was no statistical difference of C-fos protein positive cells between group B and group A(P>0.05),C-fos protein positive cells level of group B was significantly lower than that of group A(P<0.05).The binoculus C-fos protein positive cells level of groups B and C were significantly higher than that of control group at P35,P4S and P120 with statistically significant differences(P<0.05).Conclusions:The increasing of C-fos expression in geniculate body and visual cortex neurons of adult amblyopia suggests the visual cortex neurons exist a certain degree of visual plasticity.展开更多
基金supported by the National Key Research and Development Program of China (Grant No. 2018YFC0809302)the National Natural Science Foundation of China (Grant Nos. 61988101,61751305 and 61673176)+1 种基金the Fundamental Research Funds for the Central Universities (Grant No.JKH012016011)the Programme of Introducing Talents of Discipline to Universities (the “111” Project)(Grant No. B17017)。
文摘Depth information is important for autonomous systems to perceive environments and estimate their own state. Traditional depth estimation methods, like structure from motion and stereo vision matching, are built on feature correspondences of multiple viewpoints. Meanwhile, the predicted depth maps are sparse. Inferring depth information from a single image(monocular depth estimation) is an ill-posed problem. With the rapid development of deep neural networks, monocular depth estimation based on deep learning has been widely studied recently and achieved promising performance in accuracy. Meanwhile, dense depth maps are estimated from single images by deep neural networks in an end-to-end manner. In order to improve the accuracy of depth estimation, different kinds of network frameworks, loss functions and training strategies are proposed subsequently. Therefore, we survey the current monocular depth estimation methods based on deep learning in this review. Initially, we conclude several widely used datasets and evaluation indicators in deep learning-based depth estimation. Furthermore, we review some representative existing methods according to different training manners: supervised, unsupervised and semi-supervised. Finally, we discuss the challenges and provide some ideas for future researches in monocular depth estimation.
基金supported by the National Natural Science Foundation of China(Nos.61473307,61304120)
文摘Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental condi- tions, without using a set of infrared light emitting diodes （LEDs） on the parachute part of the dro- gue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effective- ness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.
文摘This article proposes a monocular trajectory intersection method,a videometrics measurement with a mature theoretical system to solve the 3D motion parameters of a point target.It determines the target’s motion parameters including its 3D trajectory and velocity by intersecting the parametric trajectory of a motion target and series of sight-rays by which a motion camera observes the target,in contrast with the regular intersection method for 3D measurement by which the sight-rays intersect at one point.The method offers an approach to overcome the technical failure of traditional monocular measurements for the 3D motion of a point target and thus extends the application fields of photogrammetry and computer vision.Wide application is expected in passive observations of motion targets on various mobile beds.
基金This work was supported in part by the National Natural Science Foundation of China(Nos.61803025,62073031)the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)(No.FRF-IDRY-19010)the Beijing Top Discipline for Artificial Intelligent Science and Engineering,University of Science and Technology Beijing.
文摘The flapping-wing air vehicle(FWAV)is a kind of bio-inspired robot whose wings can flap up and down like bird and insect wings.A vision-based obstacle avoidance method for FWAVs is proposed in this paper.First,the Farneback algorithm is used to calculate the optical flow field of the first-view video frames taken by the on-board image transmission camera.Based on the optical flow information,a fuzzy obstacle avoidance controller is then designed to generate the FWAV steering commands.Experimental results show that the proposed obstacle avoidance method can accurately identify obstacles and achieve obstacle avoidance for FWAVs.
文摘Objective:To explore the changes of lateral geniculate body and visual cortex in monocular strabismus and form deprived amblyopic rat,and visual development plastic stage and visual plasticity in adult rats.Methods:A total of 60 SD rats ages 13 d were randomly divided into A,B,C three groups with 20 in each group,group A was set as the normal control group without any processing,group B was strabismus amblyopic group,using the unilateral extraocular rectus resection to establish the strabismus amblyopia model,group C was monocular form deprivation amblyopia group using unilateral eyelid edge resection+lid suture.At visual developmental early phase(P2S),meta phase(P3S),late phase(P45)and adult phase(P120),the lateral geniculate body and visual cortex area 17 of five rats in each group were exacted for C-fos Immunocytochemistry.Neuron morphological changes in lateral geniculate body and visual cortex was observed,the positive neurons differences of C-fos expression induced by light stimulation was measured in each group,and the condition of radiation development of P120 amblyopic adult rats was observed.Results:In groups B and C,C-fos positive cells were significantly lower than the control group at P25(P<0.05),there was no statistical difference of C-fos protein positive cells between group B and group A(P>0.05),C-fos protein positive cells level of group B was significantly lower than that of group A(P<0.05).The binoculus C-fos protein positive cells level of groups B and C were significantly higher than that of control group at P35,P4S and P120 with statistically significant differences(P<0.05).Conclusions:The increasing of C-fos expression in geniculate body and visual cortex neurons of adult amblyopia suggests the visual cortex neurons exist a certain degree of visual plasticity.
