Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Industrial and Manufacturing Engineering
22
Scopus Publications
879
Scholar Citations
12
Scholar h-index
14
Scholar i10-index
Scopus Publications
Do Planar Constraints Improve Camera Pose Estimation in Monocular SLAM? Charlotte Arndt, Reza Sabzevari, Javier Civera Proceedings 2023 IEEE Cvf International Conference on Computer Vision Workshops Iccvw 2023, 2023 Geometric structures such as lines and planes are relevant in SLAM, as they improve the map interpretability and usability for downstream tasks. Planar landmarks add structural constraints to the map optimization, which could improve the accuracy of camera pose estimates. However, does the latter really happen in practice? In this paper, we thoroughly evaluate the effect of adding planar constraints in monocular SLAM, both in simulated and real scenes. Our experiments show that, in practical use cases, the benefit of adding such planar constraint shows benefits for scene estimation but limited effect in the camera pose estimation.
From points to planes - Adding planar constraints to monocular SLAM factor graphs Charlotte Arndt, Reza Sabzevari, Javier Civera IEEE International Conference on Intelligent Robots and Systems, 2020 Planar structures are common in man-made environments. Their addition to monocular SLAM algorithms is of relevance in order to achieve more complete and higher- level scene representations. Also, the additional constraints they introduce might reduce the estimation errors in certain situations. In this paper we present a novel formulation to incorporate plane landmarks and planar constraints to feature- based monocular SLAM. Specifically, we enforce in-plane points to lie exactly in the plane they belong to, propagating such information to the rest of the states. Our formulation, differently from the state of the art, allows us to incorporate general planes, independently of depth information or CNN segmentation being available (although we could also use them). We evaluate our method in several sequences of public databases, showing accurate plane estimations and pose accuracy on par with state- of-the-art point-only monocular SLAM.
An information gain formulation for active volumetric 3D reconstruction Stefan Isler, Reza Sabzevari, Jeffrey Delmerico, Davide Scaramuzza Proceedings IEEE International Conference on Robotics and Automation, 2016 We consider the problem of next-best view selection for volumetric reconstruction of an object by a mobile robot equipped with a camera. Based on a probabilistic volumetric map that is built in real time, the robot can quantify the expected information gain from a set of discrete candidate views. We propose and evaluate several formulations to quantify this information gain for the volumetric reconstruction task, including visibility likelihood and the likelihood of seeing new parts of the object. These metrics are combined with the cost of robot movement in utility functions. The next best view is selected by optimizing these functions, aiming to maximize the likelihood of discovering new parts of the object. We evaluate the functions with simulated and real world experiments within a modular software system that is adaptable to other robotic platforms and reconstruction problems. We release our implementation open source.
Multi-body Motion Estimation from Monocular Vehicle-Mounted Cameras Reza Sabzevari, Davide Scaramuzza IEEE Transactions on Robotics, 2016 This paper addresses the problem of simultaneous estimation of a vehicle's ego motion and motions of multiple moving objects in the scene-called eoru motions-through a monocular vehicle-mounted camera. Localization of multiple moving objects and estimation of their motions is crucial for autonomous vehicles. Conventional localization and mapping techniques (e.g., visual odometry and simultaneous localization and mapping) can only estimate the ego motion of the vehicle. The capability of a robot localization pipeline to deal with multiple motions has not been widely investigated in the literature. We present a theoretical framework for robust estimation of multiple relative motions in addition to the camera ego motion. First, the framework for general unconstrained motion is introduced and then it is adapted to exploit the vehicle kinematic constraints to increase efficiency. The method is based on projective factorization of the multiple-trajectory matrix. First, the ego motion is segmented and then several hypotheses are generated for the eoru motions. All the hypotheses are evaluated and the one with the smallest reprojection error is selected. The proposed framework does not need any a priori knowledge of the number of motions and is robust to noisy image measurements. The method with a constrained motion model is evaluated on a popular street-level image dataset collected in urban environments (the KITTI dataset), including several relative ego-motion and eoru-motion scenarios. A benchmark dataset (Hopkins 155) is used to evaluate this method with a general motion model. The results are compared with those of the state-of-the-art methods considering a similar problem, referred to as multibody structure from motion in the computer vision community.
Natural lecithin promotes neural network complexity and activity Shahrzad Latifi, Ali Tamayol, Rouhollah Habibey, Reza Sabzevari, Cyril Kahn, et al. Scientific Reports, 2016 Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called “essential” fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications.
Monocular simultaneous multi-body motion segmentation and reconstruction from perspective views Reza Sabzevari, Davide Scaramuzza Proceedings IEEE International Conference on Robotics and Automation, 2014 In this paper, we tackle the problem of mapping multiple 3D rigid structures and estimating their motions from perspective views through a car-mounted camera. The proposed method complements conventional localization and mapping algorithms (such as Visual Odometry and SLAM) to estimate motions of other moving objects in addition to the vehicle's motion. We present a theoretical framework for robust estimation of multiple motions and structures from perspective images. The method is based on the factorization of the projective trajectory matrix without explicit estimation of projective depth values. We exploit the epipolar geometry of calibrated cameras to generate several hypotheses for motion segments. Once the hypotheses are obtained, they are evaluated in an iterative scheme by alternating between estimation of 3D structures and estimation of multiple motions. The proposed framework does not require any knowledge about the number of motions and is robust to noisy image measurements. The method is evaluated on street-level sequences from a car-mounted camera. A benchmark dataset is also used to compare the results with previous works, although most of the related works use synthetic scenes simulating desktop environments.
Piecewise single view Photometric Stereo with multi-view constraints Reza Sabzevari, Alessio Del Bue, Vittorio Murino Proceedings International Conference on Image Processing Icip, 2012 This paper presents a novel Photometric Stereo approach for static views that recasts the problem into a piecewise formulation. The proposed algorithm, called Piecewise Photometric Stereo (PPS), entails several advantages in respect to previous global approaches. It is intrinsically more efficient, since reconstructing the surface in patches is computationally faster than reconstructing the global surface. Each patch has been associated an individual photometric model rather than a single global model as used in classical approaches. In this way, the piecewise formulation may grasp more complex lighting effects. Finally, the global metric properties of the shape is preserved using the multi-view constraints. In this pipeline, structure from motion is exploited to define such set of constraints and to compose a 3D mesh representing the metric structure of the object. Real results with ground truth show the positive performance of our algorithm compared with a classical global approach for Photometric Stereo.
Multi-view photometric stereo using semi-isometric mappings Reza Sabzevari, Alessio Del Bue, Vittorio Murino Proceedings 2nd Joint 3dim 3dpvt Conference 3D Imaging Modeling Processing Visualization and Transmission 3dimpvt 2012, 2012 Classical uncalibrated Photometric Stereo approaches are mostly constrained to the static view assumption that enforces the camera to be fixed in front of an object illuminated by different light sources. Attempts to extend PS to multi-views has delivered methods that can only be robust to images taken with short camera baselines. In this paper, we present a new uncalibrated Multi-View Photometric Stereo (MVPS) method that can obtain a dense 3D reconstruction from views subject to strong baseline variations and extreme changes in illumination conditions. This approach is intrinsically photo geometric obtaining robust results using a combination of multi-view geometry and photometry. At the core of the algorithm, there is an efficient planar embedding and local image pixel registration among views that renders the problem tractable and computationally solvable. In the experiments, the results are evaluated and compared with the existing methods as well as the ground truth and shows the method is able to deal with the most complex objects and lighting conditions.
Introducing a sensor network for advanced driver assistance systems using fuzzy logic and sensor data fusion techniques Ad Hoc and Sensor Wireless Networks, 2009
Employing ANFIS for Object detection in Robo-Pong Proceedings of the 2008 International Conference on Artificial Intelligence Icai 2008 and Proceedings of the 2008 International Conference on Machine Learning Models Technologies and Applications, 2008
Enhancement in Two-Phase OSD learning method for RBF Neural Networks Proceedings of the 2008 International Conference on Artificial Intelligence Icai 2008 and Proceedings of the 2008 International Conference on Machine Learning Models Technologies and Applications, 2008
An intelligent data mining approach using neuro-rough hybridization to discover hidden knowledge from information systems Journal of Information Science and Engineering, 2008
Design of a new urban traffic control system using modified ant colony optimization approach Iranian Journal of Science and Technology Transaction B Engineering, 2008
An intelligent vision system on a mobile manipulator International Journal of Engineering Transactions A Basics, 2008
Intelligent parameter reduction using rough sets theory and sensitivity analysis Wseas Transactions on Systems, 2007
Expert clustering of hydraulic-geotechnical control parameters of rubble mound breakwaters using rough sets theory International Conference on Computational Intelligence Man Machine Systems and Cybernetics Proceedings, 2006
RECENT SCHOLAR PUBLICATIONS
Robot and method for ascertaining a distance traveled by a robot R Sabzevari US Patent 12,588,584 , 2026 2026
System and method for detecting virtual points and ascertaining virtual planes for autonomous navigation of a movable robotic unit, and robotic system including the robotic unit R Sabzevari, C Arndt, J Civera US Patent 12,124,268 , 2024 2024
Method for determining objects in an environment for slam C Juette, N Vaskevicius, P Biber, R Sabzevari, S Benz, T Linder US Patent App. 18/331,351 , 2024 2024 Citations: 2
Do planar constraints improve camera pose estimation in monocular slam? C Arndt, R Sabzevari, J Civera Proceedings of the IEEE/CVF International Conference on Computer Vision … , 2023 2023 Citations: 4
From points to planes-adding planar constraints to monocular SLAM factor graphs C Arndt, R Sabzevari, J Civera 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems … , 2020 2020 Citations: 32
A comparison of volumetric information gain metrics for active 3D object reconstruction J Delmerico, S Isler, R Sabzevari, D Scaramuzza Autonomous Robots 42 (2), 197-208 , 2018 2018 Citations: 216
Multi-body motion estimation from monocular vehicle-mounted cameras R Sabzevari, D Scaramuzza IEEE Transactions on Robotics 32 (3), 638-651 , 2016 2016 Citations: 76
Natural lecithin promotes neural network complexity and activity S Latifi, A Tamayol, R Habibey, R Sabzevari, C Kahn, D Geny, ... Scientific reports 6 (1), 25777 , 2016 2016 Citations: 60
An Information Gain Formulation for Active Volumetric 3D Reconstruction S Isler, R Sabzevari, J Delmerico, D Scaramuzza IEEE International Conference on Robotics and Automation (ICRA2016) , 2016 2016 Citations: 259
LightPanel: Active Mobile Platform for Dense 3D Modelling J Schuler, R Sabzevari, D Scaramuzza arXiv preprint arXiv:1506.04904 , 2015 2015
PHENOM: Interest Points on Photometric Normal Maps. R Sabzevari, E Alak, D Scaramuzza Eurographics (Posters), 19-20 , 2015 2015 Citations: 3
PiMPeR: Piecewise dense 3D reconstruction from multi-view and multi-illumination images R Sabzevari, V Murino, A Del Bue arXiv preprint arXiv:1503.04598 , 2015 2015 Citations: 1
A Novel Bioinspired Nanoparticle Promotes Neurite outgrowth and Increases Neural Network Activity in Primary Neuronal Cultures S Latifi, F Cesca, A Tamayol, R Habibi, R Sabzevari, A Blau, M Linder, ... Society for Neuroscience annual meeting, Washington, DC, USA , 2014 2014
Monocular Simultaneous Multi-Body Motion Segmentation and Reconstruction from Perspective Views R Sabzevari, D Scaramuzza IEEE International Conference on Robotics and Automation (ICRA'14), 23-30 , 2014 2014 Citations: 23
Nanoscale Characterization of Nano-Liposome as Drug Delivery In vitro E Arab-Tehrany, S Latifi, R Sabzevari, D Geny, M Linder Drug Discovery & Therapy World Congress (DDTWC2013) , 2013 2013
Photo-geometric dense 3D reconstruction from uncalibrated images. R Sabzevari 2013
Multi-view Photometric Stereo using Semi-isometric Mappings R Sabzevari, A Del Bue, V Murino International Conference on 3D Imaging, Modeling, Processing, Visualization … , 2012 2012 Citations: 4
Piecewise Single View Photometric Stereo with Multi-View Constraints R Sabzevari, A Del Bue, V Murino IEEE International Conference on Image Processing (ICIP2012), 21-24 , 2012 2012 Citations: 1
Combining Structure from Motion and Photometric Stereo: A Piecewise Formulation R Sabzevari, A Del Bue, V Murino Eurographics 2012, 33-34 , 2012 2012 Citations: 2
Structure from motion and photometric stereo for dense 3D shape recovery R Sabzevari, A Del Bue, V Murino 16th International Conference of Image Analysis and Processing – ICIAP2011 … , 2011 2011 Citations: 12
MOST CITED SCHOLAR PUBLICATIONS
An Information Gain Formulation for Active Volumetric 3D Reconstruction S Isler, R Sabzevari, J Delmerico, D Scaramuzza IEEE International Conference on Robotics and Automation (ICRA2016) , 2016 2016 Citations: 259
A comparison of volumetric information gain metrics for active 3D object reconstruction J Delmerico, S Isler, R Sabzevari, D Scaramuzza Autonomous Robots 42 (2), 197-208 , 2018 2018 Citations: 216
Multi-body motion estimation from monocular vehicle-mounted cameras R Sabzevari, D Scaramuzza IEEE Transactions on Robotics 32 (3), 638-651 , 2016 2016 Citations: 76
Natural lecithin promotes neural network complexity and activity S Latifi, A Tamayol, R Habibey, R Sabzevari, C Kahn, D Geny, ... Scientific reports 6 (1), 25777 , 2016 2016 Citations: 60
Three-phase strategy for the OSD learning method in RBF neural networks GA Montazer, R Sabzevari, F Ghorbani Neurocomputing 72 (7-9), 1797-1802 , 2009 2009 Citations: 35
Multisensor Data Fusion Strategies for Advanced Driver Assistance Systems MR Ghahroudi, R Sabzevari Sensor and Data Fusion, 141-166 , 2009 2009 Citations: 33
From points to planes-adding planar constraints to monocular SLAM factor graphs C Arndt, R Sabzevari, J Civera 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems … , 2020 2020 Citations: 32
Improvement of learning algorithms for RBF neural networks in a helicopter sound identification system GA Montazer, R Sabzevari, HGP Khatir Neurocomputing 71 (1-3), 167-173 , 2007 2007 Citations: 31
Monocular Simultaneous Multi-Body Motion Segmentation and Reconstruction from Perspective Views R Sabzevari, D Scaramuzza IEEE International Conference on Robotics and Automation (ICRA'14), 23-30 , 2014 2014 Citations: 23
Design of a new urban traffic control system using modified ant colony optimization approach R Foroughi, GA Montazer, R Sabzevari Iranian Journal of Science and Technology-Transaction B: Engineering 32 (B2 … , 2008 2008 Citations: 18
Employing ANFIS for object detection in robo-pong R Sabzevari, S Masoumzadeh, MR Ghahroudi International Conference on Artificial Intelligence - ICAI'08, 707-712 , 2008 2008 Citations: 16
Structure from motion and photometric stereo for dense 3D shape recovery R Sabzevari, A Del Bue, V Murino 16th International Conference of Image Analysis and Processing – ICIAP2011 … , 2011 2011 Citations: 12
Object detection and localization system based on neural networks for Robo-Pong R Sabzevari, A Shahri, AR Fasih, S Masoumzadeh, MR Ghahroudi 5th International Symposium on Mechatronics and Its Applications - ISMA08, 1-6 , 2008 2008 Citations: 12
Intelligent parameter reduction using rough sets theory and sensitivity analysis GA Montazer, R Sabzevari, HGP Khatir WSEAS Transactions on Systems 6 (3), 623-630 , 2007 2007 Citations: 10
Introducing a Sensor Network for Advanced Driver Assistance Systems Using Fuzzy Logic and Sensor Data Fusion Techniques MR Ghahroudi, M Sarshar, R Sabzevari International Journal of Ad Hoc & Sensor Wireless Network 8 (1-2), 35-55 , 2009 2009 Citations: 6
An Intelligent Vision System on a Mobile Manipulator MH Korayem, V Ehtemam, R Sabzevari, M Madani, V Azimirad International Journal of Engineering-Transaction A: Basics 3 (21), 279-294 , 2008 2008 Citations: 5
A Novel Content-Based Image Retrieval Technique Using Tree Matching MR Ghahroudi, MR Sarshar, R Sabzevari International Conference of Signal and Image Engineering - ICSIE'08 3, 1797-1801 , 2008 2008 Citations: 5
Do planar constraints improve camera pose estimation in monocular slam? C Arndt, R Sabzevari, J Civera Proceedings of the IEEE/CVF International Conference on Computer Vision … , 2023 2023 Citations: 4
Multi-view Photometric Stereo using Semi-isometric Mappings R Sabzevari, A Del Bue, V Murino International Conference on 3D Imaging, Modeling, Processing, Visualization … , 2012 2012 Citations: 4
An Intelligent Data Mining Approach Using Neuro-Rough Hybridization to Discover Hidden Knowledge from Information Systems R Sabzevari, GA Montazer Journal of Information Science and Engineering 24 (4), 1111-1126 , 2008 2008 Citations: 4
