Image analysis – Applications – Target tracking or detecting
Reexamination Certificate
2006-07-13
2008-10-28
Azarian, Seyed (Department: 2624)
Image analysis
Applications
Target tracking or detecting
C382S170000, C348S169000
Reexamination Certificate
active
07444003
ABSTRACT:
The present invention relates to an apparatus for rapidly analyzing frame(s) of digitized video data which may include objects of interest randomly distributed throughout the video data and wherein said objects are susceptible to detection, classification, and ultimately identification by filtering said video data for certain differentiable characteristics of said objects. The present invention may be practiced on pre-existing sequences of image data or may be integrated into an imaging device for real-time, dynamic, object identification, classification, logging/counting, cataloging, retention (with links to stored bitmaps of said object), retrieval, and the like. The present invention readily lends itself to the problem of automatic and semi-automatic cataloging of vast numbers of objects such as traffic control signs and utility poles disposed in myriad settings. When used in conjunction with navigational or positional inputs, such as GPS, an output from the inventative systems indicates the identity of each object, calculates object location, classifies each object by type, extracts legible text appearing on a surface of the object (if any), and stores a visual representation of the object in a form dictated by the end user/operator of the system. The output lends itself to examination and extraction of scene detail, which cannot practically be successfully accomplished with just human viewers operating video equipment, although human intervention can still be used to help judge and confirm a variety of classifications of certain instances and for types of identified objects.
REFERENCES:
patent: 5392365 (1995-02-01), Steinkirchner
patent: 5448484 (1995-09-01), Bullock et al.
patent: 5465115 (1995-11-01), Conrad et al.
patent: 5465308 (1995-11-01), Hutcheson et al.
patent: 5627915 (1997-05-01), Rosser et al.
patent: 5633944 (1997-05-01), Guibert et al.
patent: 5633946 (1997-05-01), Lachinski et al.
patent: 5696503 (1997-12-01), Nasburg
patent: 5699444 (1997-12-01), Palm
patent: 5740274 (1998-04-01), Ono et al.
patent: 5790691 (1998-08-01), Narayanswamy et al.
patent: 5844699 (1998-12-01), Usami et al.
patent: 5864630 (1999-01-01), Cosatto et al.
patent: 5892847 (1999-04-01), Johnson
patent: 5949914 (1999-09-01), Yuen
patent: 5974521 (1999-10-01), Akerib
patent: 5991085 (1999-11-01), Rallison et al.
patent: 6018697 (2000-01-01), Morimoto et al.
patent: 6064768 (2000-05-01), Hajj et al.
patent: 6141433 (2000-10-01), Moed et al.
patent: 6141434 (2000-10-01), Christian et al.
patent: 6405132 (2002-06-01), Breed et al.
patent: 6424914 (2002-07-01), Lin
J. Patrick Bixler, Department of Computer Science, Virginia Tech, Blacksburg, Virginia; David P. Miller Artificial Intelligence Group, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, “Extracting text from real-world scenes”, Article, 8 pp., 1988.
Dominant Color Transform and Circular Pattern Vector for Traffic Sign Detection and Recognition, Jung Hak and Tae Young Choi, IEICE Transaction Fundamentals, vol. E81-A, No. 6, pp. 1128-1135, Jun. 1998.
A Trainable Pedestrian Detection System, C. Papageorgiou, T. Evgenious, T. Poggio, Center for Biological And Computational Learning and Artificial Intelligence Laboratory, MIT, IEEE International Conference on Intelligent Vehicles, pp. 241-246, 1998.
Robust Lane Recognition Embedded in a Real-Time Driver Assistance System, R. Risack, P. Klausmann, W. Kruger, W. Enkelmann, Fraunhofer-Institut fur Informations, Karlsruhe, Germany, IEEE International Conference on Intelligent Vehicles, pp. 35-40, 1998.
A Texture-based Object Detection and an Adaptive Model-based Classification, T. Kalinke, C. Tzomakas, W. Seelen, Institut fur Neuroinformatik, Bochum, Germany, IEEE International Conference on Intelligent Vehicles, pp. 143-148, 1998.
Internet Printout: The Road Sign Recognition System—RS.sup.2, Faculty of Transportation Sciences, Prague, Czech Republic, 7 pgs., c. approximately 1999.
Internet Printout: The Chamfer System, 4 pgs., c. approximately 1999.
Real-Time Object Recognition: Hierarchical Image Matching in a Parallel Virtual Machine Environment, J. You, P. Bhattacharya, S. Hungenahally, School of Computing and Information Technology, Griffith University, Brisbane, Australia, Dept. of Computer Engineering, University of Nebraska, Lincoln, Nebraska, 3 pgs., undated. (1994).
An Architecture of Object Recognition System for Various Images Based on Multi-Agent, Keiji Yanai, Koichiro Deguchi, Dept. of Computer Science, University of Electro-Communications, Tokyo, Japan, and Dept. of Mathematical Engineering and Information Physics, University of Tokyo, Tokyo, Japan, 4 pgs., undated. (1998).
Multi-Feature Matching Algorithm for Free-Form 3D Surface Registration, C. Schutz, T. Jost, H, Hugli, Institute for Microtechnology, Neuchatel, Switzerland, 3 pgs., undated. (Aug. 1998).
Representation of Uncertainty in Spatial Target Tracking, Tim Baker, Malcolm Strens, DERA Farnborough, United Kingdom, 4 pgs., undated. (1998).
Using Centroid Covariance in Target Recognition, Gang Liu and Robert M. Haralick, Dept. of Electrical Engineering, University ofWashington, Seattle, Washington, 4 pgs., undated. (1998).
Using Spatial Sorting and Ranking in Model Based Object Recognition, G. Hjaltason, M. Ray, H. Samet, I. Weiss, Computer Science Dept. University of Maryland, College Park, Maryland, 3 pgs., undated. (Aug. 1998).
Surveillance Systems for Terrestrial Transport Safety and Improved User Information Capability, C. Nwagboso, C. Regazzoni, M. Renard, E. Stringa, Bolton Institute, Bolton, United Kingdom, Dept. of Biophysical & Electronic Engineering, Genova, Italy, Vigitec, Brussels, Belgium, pp. 1-7, undated. (1998).
Landmark Recognition using Projection Learning for Mobile Robot Navigation, Ren C. Luo, Harsh Potlapalli, Center for Robotics and Intelligent Machines, IEEE World Congress on Computational Intelligence, vol. IV, pp. 2703-2708, Jun. 1994.
A Real-Time Traffic Sign Recognition System, S. Estable, J. Schick, F. Stein, R. Janssen, R. Ott, W. Ritter, Y.-J. Zheng, Daimler-Benz Research Center, Proceedings of the Intelligent Vehicles '94 Symposium, Paris, France, pp. 213-218, Oct. 1994.
Recognition of Traffic Signs by Artificial Neural Network, D. Ghica, S. Lu, X. Yuan, Dept. of Computer Science Memorial University of Newfoundland, IEEE, pp. 1444-1449, Mar. 1995.
Realtime Traffic Sign Recognition (TSR), Jens Logemann, Ed., Univeritat Koblenz-Landau, 3 pgs., Nov. 1997.
Registering Multiple Cartographic Models with the Hierarchical Mixture of Experts Algorithm, Simon Moss and Edwin R. Hancock, Dept. of Computer Science, University of New York, IEEE, pp. 909-914, 1997.
Multi-Modal Tracking of Faces for Video Communications, James L. Crowley and Francois Berard, GRAVIR—IMAG, I.N.P. Grenoble, Grenoble, France, IEEE, pp. 640-645, 1997.
Road Traffic Sign Detection and Classification, A. Escalera, L. Moreno, M. Salichs, J. Armingol, IEEE Transactions on Industrial Electronics, vol. 44, No. 6, pp. 848-859, Dec. 1997.
Auto-associative Segmentation for Real-Time Object Recognition in Realistic Outdoor Images, Leonardo Estevez and Nasser Kehtarnavaz, Dept. of Electricial Engineering, Texas A&M University, Journal of Electronic Imaging, vol. 72, pp. 378-385, Apr. 1998.
Mandal, “Illumination Invariant Image Indexing Using Moments and Wavelets” Journal of Electronic Imaging, Apr. 1998 pp. 282-293, vol. 7 (2), USA.
Celentano, “Feature Integration and Relevance Feedback Analysis in Image Similarity Evaluation” Journal of Electronic Imaging, Apr. 1998, pp. 308-317 vol. 7(2), USA.
Estevez, Auto-Associatve Segmentation for Real-Time Object Recognition in Realistic Outdoor Images, Journal of Electronic Imaging, Apr. 1998 pp. 378-385 vol. 7(2), USA.
Feature Integration and Relevancy Feedback Analysis in Image Similarity Evaluation, Celentano, Journal of Electronic Imaging, vol. 7 (2), pp. 308-317, Apr. 1998.
Laumeyer Robert A.
Retterath Jamie E.
Azarian Seyed
Facet Technology Corporation
Patterson Thuente Skaar & Christensen P.A.
LandOfFree
Method and apparatus for identifying objects depicted in a... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method and apparatus for identifying objects depicted in a..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and apparatus for identifying objects depicted in a... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-4012372