- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Stereo-Matching Network for Structured Light
摘要： Recently, deep learning has been widely applied in binocular stereo matching for depth acquisition, which has led to an immense increase of accuracy. However, little attention has been paid to the structured light ?eld. In this letter, a network for structured light is proposed to extract effective matching features for depth acquisition. The proposed network promotes the Siamese network by considering receptive ?elds of different scales and assigning proper weights to the corresponding features, which is achieved by combining pyramid-pooling structure with the squeeze-and-excitation network into the Siamese network for feature extraction and weight calculations, respectively. For network training and testing, a structured-light dataset with amended ground truths is generated by projecting a random pattern into the existing binocular stereo dataset. Experiments demonstrate that the proposed network is capable of real-time depth acquisition, and it provides superior depth maps using structured light.
关键词： SLNet,stereo matching,Structured light,siamese network
更新于2025-09-23 15:23:52
-
[IEEE 2018 15th Conference on Computer and Robot Vision (CRV) - Toronto, ON, Canada (2018.5.8-2018.5.10)] 2018 15th Conference on Computer and Robot Vision (CRV) - Disparity Filtering with 3D Convolutional Neural Networks
摘要： Stereo matching is an ill-posed problem and hence the disparity maps generated are often inaccurate and noisy. To alleviate the problem, a number of approaches were proposed to output accurate disparity values for selected pixels only. Instead of designing another disparity optimization method for sparse disparity matching, we present a novel disparity filtering step that detects and removes inaccurate matches. Based on 3D convolutional neutral networks, our detector is trained directly on 3D matching cost volumes and hence can work with different matching cost generation approaches. The experimental results show that it can effectively filter out mismatches while preserving the accurate ones. As a result, combining our approach with the simplest Winner-Take-All optimization will lead to a better performance than most existing sparse stereo matching algorithms on the Middlebury Stereo Evaluation site.
关键词： stereo matching,confidence measure,3D CNNs
更新于2025-09-23 15:23:52
-
3-D People Counting with a Stereo Camera on GPU Embedded Board
摘要： People counting in surveillance cameras is a key technology for understanding the flow population and generating heat maps. In recent years, people detection performance has been greatly improved with the development of object detection algorithms using deep learning. However, in places where people are crowded, the detection rate is low as people are often occluded by other people. We proposed a people-counting method using a stereo camera to resolve the non-detection problem due to the occlusion. We applied stereo matching to extract the depth image and convert the camera view to top view using depth information. People were detected using a height map and an occupancy map, and people were tracked and counted using a Kalman filter-based tracker. We operated the proposed method on the NVIDIA Jetson TX2 to check the real-time operation possibility on the embedded board. Experimental results showed that the proposed method had higher accuracy than the existing methods and that real-time processing is possible.
关键词： NVIDIA Jetson TX2,occlusion,view projection,stereo matching,Kalman filter tracker,3-D people counting
更新于2025-09-23 15:22:29
-
[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Depth Estimation with Occlusion Handling from a Sparse Set of Light Field Views
摘要： This paper addresses the problem of depth estimation for every viewpoint of a dense light field, exploiting information from only a sparse set of views. This problem is particularly relevant for applications such as light field reconstruction from a subset of views, for view synthesis and for compression. Unlike most existing methods for scene depth estimation from light fields, the proposed algorithm computes disparity (or equivalently depth) for every viewpoint taking into account occlusions. In addition, it preserves the continuity of the depth space and does not require prior knowledge on the depth range. The experiments show that, both for synthetic and real light fields, our algorithm achieves competitive performance to state-of-the-art algorithms which exploit the entire light field and usually generate the depth map for the center viewpoint only.
关键词： light field,stereo matching,optical flow,low rank approximation,depth estimation
更新于2025-09-23 15:22:29
-
[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Real-Time 3D Reconstruction in Minimally Invasive Surgery with Quasi-Dense Matching
摘要： In this work, a method for 3D reconstruction of Minimally Invasive Surgery data in real-time is presented. It is formulated on top of the already established framework of Quasi-Dense Matching, optimizing its components for speed. First, it recovers a set of sparse features, which are matched robustly. Then, 3D information is propagated in a spatial neighbourhood, until similarity reaches a prede?ned threshold, to cover a semi-dense portion of operating ?eld domain. Matching on dense level is achieved with Zero Mean Normalized Cross Correlation metric to establish correspondences. The algorithm is able to recover disparity maps with relatively small error, while maintaining real-time performance.
关键词： CUDA,MIS,Disparity Estimation,Stereo Matching,3D Reconstruction
更新于2025-09-23 15:22:29
-
[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Robust Facial Pose Estimation Using Landmark Selection Method for Binocular Stereo Vision
摘要： In this paper, we present a robust framework for facial pose estimation from binocular stereoscopic vision. Unlike prior work on the facial pose estimation that employs the whole landmarks even located in the wrong position, we propose a landmark selection method to remove the erroneous landmarks for better performance, especially in the large facial pose case. For this purpose, we train a convolutional neural network (CNN) in order to measure the con?dence of each facial landmark detected by using a well-known landmark detection algorithm. Also, by ?tting selected landmarks to 3D space, our framework becomes more robust even when a small number of landmarks are selected. Due to the absence of public dataset for the binocular stereo facial pose, we construct facial pose datasets using a motion sensor for performance validation. In our experiments, our method achieves the higher accuracy of the pose estimation than the previous method, especially for large facial pose cases.
关键词： Binocular stereo vision,Facial landmarks,Facial pose estimation,Stereo matching algorithm
更新于2025-09-23 15:21:01
-
Underwater Target Detection and 3D Reconstruction System Based on Binocular Vision
摘要： To better solve the problem of target detection in marine environment and to deal with the difficulty of 3D reconstruction of underwater target, a binocular vision-based underwater target detection and 3D reconstruction system is proposed in this paper. Two optical sensors are used as the vision of the system. Firstly, denoising and color restoration are performed on the image sequence acquired by the vision of the system and the underwater target is segmented and extracted according to the image saliency using the super-pixel segmentation method. Secondly, aiming to reduce mismatch, we improve the semi-global stereo matching method by strictly constraining the matching in the valid target area and then optimizing the basic disparity map within each super-pixel area using the least squares fitting interpolation method. Finally, based on the optimized disparity map, triangulation principle is used to calculate the three-dimensional data of the target and the 3D structure and color information of the target can be given by MeshLab. The experimental results show that for a specific size underwater target, the system can achieve higher measurement accuracy and better 3D reconstruction effect within a suitable distance.
关键词： underwater target detection,binocular vision,disparity map optimization,semi-global stereo matching,3D reconstruction
更新于2025-09-23 15:21:01
-
[IEEE 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - Sozopol, Bulgaria (2019.9.6-2019.9.8)] 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - A Resonance-Type Terahertz-Frequency Signal Detector Based on an Antiferromagnetic Tunnel Junction
摘要： Accurate depth estimation is still an important challenge after a decade, particularly from stereo images. The accuracy comes from a good depth level and preserved structure. For this purpose, a depth post-processing framework is proposed in this paper. The framework starts with the ‘‘Adaptive Random Walk with Restart (2015)’’ algorithm. To re?ne the depth map generated by this method, we introduced a form of median solver/?lter based on the concept of the mutual structure, which refers to the structural information in both images. This ?lter is further enhanced by a joint ?lter. Next, a transformation in image domain is introduced to remove the artifacts that cause distortion in the image. The proposed post-processing method is then compared with the top eight algorithms in the Middlebury benchmark. To explore how well this method is able to compete with more widely known techniques, a comparison is performed with Google’s new depth map estimation method. The experimental results demonstrate the accuracy and ef?ciency of the proposed post-processing method.
关键词： accuracy,Stereo matching,edge preserving,depth map
更新于2025-09-23 15:19:57
-
[IEEE 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) - Shah Alam (2018.7.11-2018.7.12)] 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) - Accurate Disparity Map Estimation Based on Edge-preserving Filter
摘要： This paper proposes a new algorithm to estimate a disparity map. This map contains depth information from stereo matching process. Generally, this process is sensitive to low texture areas and high noise on images with high different brightness and contrast. To get over these problems, the proposed algorithm utilizes the RGB channels at the matching stage and edge-preserving filter at the second and final stage. The filter is known as Guided Filter (GF). The GF kernel well-recovered low texture areas which is able to reduce noise and sharpen the images. Additionally, GF is strong against the distortions due to high brightness and contrast. The propose algorithm produces accurate results on the disparity map for the low textured regions. The proposed work in this paper produces accurate results and performs much better compared to some established algorithms based on the quantitative and qualitative measurements using standard stereo benchmarking evaluation from the Middlebury.
关键词： stereo matching,sum of absolute differences,computer vision,disparity map,guided filter
更新于2025-09-19 17:15:36
-
[IEEE 2019 Photonics North (PN) - Quebec City, QC, Canada (2019.5.21-2019.5.23)] 2019 Photonics North (PN) - High Performance Monolithic Dual-Wavelength InAs/InP Quantum Dash C-Band DFB Laser
摘要： Accurate depth estimation is still an important challenge after a decade, particularly from stereo images. The accuracy comes from a good depth level and preserved structure. For this purpose, a depth post-processing framework is proposed in this paper. The framework starts with the ‘‘Adaptive Random Walk with Restart (2015)’’ algorithm. To re?ne the depth map generated by this method, we introduced a form of median solver/?lter based on the concept of the mutual structure, which refers to the structural information in both images. This ?lter is further enhanced by a joint ?lter. Next, a transformation in image domain is introduced to remove the artifacts that cause distortion in the image. The proposed post-processing method is then compared with the top eight algorithms in the Middlebury benchmark. To explore how well this method is able to compete with more widely known techniques, a comparison is performed with Google’s new depth map estimation method. The experimental results demonstrate the accuracy and ef?ciency of the proposed post-processing method.
关键词： edge preserving,Stereo matching,accuracy,depth map
更新于2025-09-19 17:13:59