Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
Model-based object pose in 25 lines of code
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Efficient Pose Clustering Using a Randomized Algorithm
International Journal of Computer Vision
Computer Vision and Image Understanding
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Hardware-Software partitioning and pipelined scheduling of transformative applications
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Long And Winding Road to High-Performance Image Processing with MMX/SSE
CAMP '00 Proceedings of the Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00)
Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers (2nd Edition)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
On Pose Recovery for Generalized Visual Sensors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cache implications of aggressively pipelined high performance microprocessors
ISPASS '04 Proceedings of the 2004 IEEE International Symposium on Performance Analysis of Systems and Software
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
Robust Pose Estimation from a Planar Target
IEEE Transactions on Pattern Analysis and Machine Intelligence
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
EPnP: An Accurate O(n) Solution to the PnP Problem
International Journal of Computer Vision
HERB: a home exploring robotic butler
Autonomous Robots
Object recognition and full pose registration from a single image for robotic manipulation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Fast Keypoint Recognition Using Random Ferns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast algorithms for bin packing
Journal of Computer and System Sciences
Monocular vision based 6D object localization for service robot's intelligent grasping
Computers & Mathematics with Applications
An assistive vision system for the blind that helps find lost things
ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II
Object recognition robust to imperfect depth data
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
International Journal of Reconfigurable Computing - Special issue on Selected Papers from the 2011 International Conference on Reconfigurable Computing and FPGAs (ReConFig 2011)
Contextually guided semantic labeling and search for three-dimensional point clouds
International Journal of Robotics Research
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We present MOPED, a framework for Multiple Object Pose Estimation and Detection that seamlessly integrates single-image and multi-image object recognition and pose estimation in one optimized, robust, and scalable framework. We address two main challenges in computer vision for robotics: robust performance in complex scenes, and low latency for real-time operation. We achieve robust performance with Iterative Clustering Estimation (ICE), a novel algorithm that iteratively combines feature clustering with robust pose estimation. Feature clustering quickly partitions the scene and produces object hypotheses. The hypotheses are used to further refine the feature clusters, and the two steps iterate until convergence. ICE is easy to parallelize, and easily integrates single- and multi-camera object recognition and pose estimation. We also introduce a novel object hypothesis scoring function based on M-estimator theory, and a novel pose clustering algorithm that robustly handles recognition outliers. We achieve scalability and low latency with an improved feature matching algorithm for large databases, a GPU/CPU hybrid architecture that exploits parallelism at all levels, and an optimized resource scheduler. We provide extensive experimental results demonstrating state-of-the-art performance in terms of recognition, scalability, and latency in real-world robotic applications.