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Special issue on 3-D image analysis and modeling

Hongbin Zha, H. Saito, V. Murino, A. Fusiello
2003 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Its goal is to obtain the geometrical structure of an observed scene, i.e., to recover reliable 3-D information from data, and to compute an efficient representation.  ...  Zhang and C. Kambhamettu proposed two systems, integrated model-based system and extended gradientbased system, to compute dense 3-D scene flow and structure from multiview image sequences.  ...  His present research is focused on image analysis, 3-D computer vision, and image-based rendering. He is a member of the International Association for Pattern Recognition (IAPR).  ... 
doi:10.1109/tsmcb.2003.814779 pmid:18238204 fatcat:h52zhkfvyvfejiv5jspemnd7ki

Real-time Object Recognition in Sparse Range Images Using Error Surface Embedding

Limin Shang, Michael Greenspan
2009 International Journal of Computer Vision  
In this work we address the problem of object recognition and localization from sparse range data.  ...  The method is based upon comparing the 7-D error surfaces of objects in various poses, which result from the registration error function between two convolved surfaces.  ...  Object Recognition with Range Images To recognize an object implies that the object model (i.e., 3-D model of the object, or a set of views of the object) are known a priori.  ... 
doi:10.1007/s11263-009-0276-3 fatcat:npcqoaxswbefxb5btmigxtqdg4

Hierarchical Scale-Based Multiobject Recognition of 3-D Anatomical Structures

U. Bagci, Xinjian Chen, J. K. Udupa
2012 IEEE Transactions on Medical Imaging  
For 1), we propose intensity weighted ball-scale object extraction concept to build a hierarchical transfer function from image space to object (shape) space such that anatomical structures in 3-D medical  ...  Segmentation of anatomical structures from medical images is a challenging problem, which depends on the accurate recognition (localization) of anatomical structures prior to delineation.  ...  Hirsch of the Department of Neurobiology and Anatomy, Drexel University, for providing the data and helping in constructing groundtruth.  ... 
doi:10.1109/tmi.2011.2180920 pmid:22203704 fatcat:bej64kdj6bfqhnyzvdtjzp4yqi

Author Index

2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
and Parsing Architecture at City Scale from Range Data Triggs, Bill Face Recognition Based on Image Sets Trinh, Hoang Workshop: Structure and Motion from Road-Driving Stereo Sequences Trinh, Nhon H.  ...  Detecting and Parsing Architecture at City Scale from Range Data Adaptive Pose Priors for Pictorial Structures Talking Pictures: Temporal Grouping and Dialog-Supervised Person Recognition Workshop  ... 
doi:10.1109/cvpr.2010.5539913 fatcat:y6m5knstrzfyfin6jzusc42p54

Active recognition through next view planning: a survey

Sumantra Dutta Roy, Santanu Chaudhury, Subhashis Banerjee
2004 Pattern Recognition  
3-D object recognition involves using image-computable features to identify 3-D object. A single view of a 3-D object may not contain sufficient features to recognize it unambiguously.  ...  We first survey important approaches to active 3-D object recognition.  ...  (Subhashis Banerjee). or 2-D intensity images. 3-D range images can be obtained from the output of a light stripe range finder, for example. 2-D images may be obtained from various means such as CCD cameras  ... 
doi:10.1016/j.patcog.2003.01.002 fatcat:mkc2hocskrd65lv7swudcslo7i

Three-Dimensional Deformable-Model-Based Localization and Recognition of Road Vehicles

Zhaoxiang Zhang, Tieniu Tan, Kaiqi Huang, Yunhong Wang
2012 IEEE Transactions on Image Processing  
We address the problem of model-based object recognition. Our aim is to localize and recognize road vehicles from monocular images or videos in calibrated traffic scenes.  ...  It is shown that the local gradient-based method can evaluate accurately and efficiently the fitness between the projection of the vehicle model and the image data.  ...  In Section IV, an efficient method based on local gradient image features is proposed to evaluate fitness between the projection of the 3-D model and image data.  ... 
doi:10.1109/tip.2011.2160954 pmid:21724513 fatcat:w56cjq5cujf2nok2xnb67xnrxy

Size Matters: Metric Visual Search Constraints from Monocular Metadata

Mario Fritz, Kate Saenko, Trevor Darrell
2010 Neural Information Processing Systems  
In this paper, we show how a crucial aspect of 3-D information-object and feature absolute size-can be added to models learned from commonly available online imagery, without use of any 3-D sensing or  ...  Metric constraints are known to be highly discriminative for many objects, but if training is limited to data captured from a particular 3-D sensor the quantity of training data may be severly limited.  ...  This work was supported in part by TOYOTA and a Feodor Lynen Fellowship granted by the Alexander von Humboldt Foundation.  ... 
dblp:conf/nips/FritzSD10 fatcat:xcat6dxwpnhn3nqd35fpihjday

Statistical Classifiers in Computer Vision [chapter]

J. Hornegger, D. Paulus, H. Niemann
1998 Studies in Classification, Data Analysis, and Knowledge Organization  
This paper introduces a unified Bayesian approach to 3-D computer vision using segmented image features.  ...  The importance of model densities is demonstrated by concrete examples. Normally distributed features are used for automatic learning, localization, and classification.  ...  and disturbed training data -, classification rules, and localization methods for 3-D objects using 2-D views.  ... 
doi:10.1007/978-3-642-72087-1_33 fatcat:kteobfdnprdbxkys4twepyc7lu

Dynamic Multi-Cue Information Fusion for Robust Detection of Traffic Infrastructure

Lucas Paletta, Gerhard Paar
2002 IAPR International Workshop on Machine Vision Applications  
Visual object detection using single cue information has been successfully applied in various tasks, in particular for near range recognition.  ...  We demonstrate preliminary work describing Bayesian decision fusion for object detection and illustrate the method by robust detection of traffic infrastructure.  ...  This work was funded from the K plus Program.  ... 
dblp:conf/mva/PalettaP02 fatcat:b4nrhels7zevdkbqlqy3vhupiq

Using spin images for efficient object recognition in cluttered 3D scenes

A.E. Johnson, M. Hebert
1999 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We present a compression scheme for spin images that results in efficient multiple object recognition which we verify with results showing the simultaneous recognition of multiple objects from a library  ...  We present a 3D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion.  ...  We would also like to thank Karun Shimoga for the use of the K 2 T sensor and Kaushik Merchant for his time spent segmenting 3D scenes.  ... 
doi:10.1109/34.765655 fatcat:i5kuma24mvarrda3clsz2m2dmq

3-D Object Recognition Using 2-D Views

Wenjing Li, G. Bebis, N.G. Bourbakis
2008 IEEE Transactions on Image Processing  
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions.  ...  Our goal is to recognize and localize instances of specific objects (i.e., model-based) in a scene.  ...  During recognition, image features are used to retrieve information from the data structure.  ... 
doi:10.1109/tip.2008.2003404 pmid:18854254 fatcat:4zeg76o2szfcbgikicqtjmovpe

Learning indexing functions for 3-D model-based object recognition

Beis, Lowe
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94  
A full 3-D recognition system has been implemented, and we present an example to demonstrate how the method works with real, cluttered images. 5O  ...  This approach has the potential to work with a wide range of image features and model types.  ...  Introduction Model-based object recognition consists of matching features between an image and a pre-stored object model.  ... 
doi:10.1109/cvpr.1994.323840 dblp:conf/cvpr/BeisL94 fatcat:5rjg4ts7ybh57pnci6h3s6ffom

Modelling and representation issues in automated feature extraction from aerial and satellite images

Arcot Sowmya, John Trinder
2000 ISPRS journal of photogrammetry and remote sensing (Print)  
The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and  ...  Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring.  ...  Acknowledgements This research was partially supported by a grant from the Australian Research Council.  ... 
doi:10.1016/s0924-2716(99)00040-4 fatcat:vbph62stangodnshczrdzyc5uy

Thrift: Local 3D Structure Recognition

Alex Flint, Anthony Dick, Anton van den Hengel
2007 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007)  
This paper presents a method for describing and recognising local structure in 3D images. The method extends proven techniques for 2D object recognition in images.  ...  The method is applied to the problem of detecting repeated structure in range images, and promising results are reported.  ...  Introduction Image based object recognition is a long standing central problem in computer vision.  ... 
doi:10.1109/dicta.2007.4426794 dblp:conf/dicta/FlintDH07 fatcat:22daavjwofaonmhtg2kld4nivu

Novel 3-D Object Recognition Methodology Employing a Curvature-Based Histogram

Liang-Chia Chen, Hoang Hong Hai, Xuan-Loc Nguyen, Hsiao-Wen Wu
2013 International Journal of Advanced Robotic Systems  
Recognition of three-dimensional (3-D) objects using range images remains one of the most challenging problems in 3-D computer vision due to its noisy and cluttered scene characteristics.  ...  objects in the scenes and then applying a process of object recognition based on geometric constraints and a curvature-based histogram for object recognition.  ...  The developed algorithm for object recognition includes two processes: • Establish the object models in a database (offline process): Dimension and curvature-based histograms of 3-D object models are constructed  ... 
doi:10.5772/56323 fatcat:tvtnvz53ibe7pal2hfhil4waly
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