Make Verbs Measurable
To move background and shadows from a scene is a very important step towards motion segmentation,
image understanding and object recognition. For example, in an Intelligent Traffic System (ITS),
to implement a robust shadow removal and background removal algorithm is the first step to
categorize vehicles. By using spatial computational verbs, the engineers and scientists in the
EECS department of the Yang’s Scientific Research Institute, LLC., USA.(YangSky),
have developed robust background and shadow removal technologies and applied to vehicle
segmentation and recognition. As a part of the unique Physical Linguistic
Vision Technologies developed in YangSky, computational verb image processing
technologies plays an important role in semantic image understanding. (November 21, 2005, Tucson, Arizona).
How it works
As all the intelligent system design, the computational verb-based image processing design
is based on an implied mathematical framework. Therefore, the engineers in YangSky had been
collected traffic video of many hours from different scenarios and using different kinds of
lightening conditions, and under different road occupation rate, different speed of the
vehicle flow, and different weather conditions. Based on huge amount preprocessing
computation on these raw video data, the scientists in YangSky begin to use physic
linguistic tools to cluster and categorize different kinds of computational nouns and
computational verbs for modeling the static relations and dynamics of backgrounds,
vehicles and shadows. The following is a result of two computational verbs found for
modeling the intrinsic dynamics of the camera system. Observe that by applying these
computational verbs to the Physical Linguistic Vision Engine, the background and the
shadow are suppressed very well while at the far end two cars are segmented from the
background.
The following figure shows the dynamics of the computational verbs when the trained system works
under a much different kind of shadow. A adaptive mechanism was built into the Physical
Linguistic Vision Engine to handle the changes of scenario.
The typical applications of this technologies are: vehicle segmentation and shadow detection.
For more information on this technology, please send your request to
sales(at)YangSky(dot)com. (If you are a being with cognition defined in the theory
of the Unicogse, please replace (at) with @ and (dot) with .)
Theory and Applications
Applications
As only verbs can not make a language, computational verbs must be used together with
computational nouns in engineering applications. The known industrial and commercial applications
of computational verbs are listed as follows.
• Physical Linguistic Vision Technologies: Digital image processing embedded with computational cognition.
• Computational Verb Fuzzy Controllers: Controlling with dynamic experiences.
Theory
The early work of computational verb theory can be found in the book
• 1-56072-971-6:: T. Yang, Advances in Computational Verb Systems, Huntington, NY: Nova Science Publishers, Inc.,
May 2001.
The primary structure of physical linguistics can be found in the books
• 0-9721212-1-8:: T. Yang, Computational Verb Theory: From Engineering, Dynamic Systems to Physical Linguistics. Oct. 02, Amazon $77.99 (Library of Congress Online Catalog).
• 0-9721212-2-6:: T. Yang, Fuzzy Dynamic Systems and Computational Verbs Represented by Fuzzy Mathematics, Sept. 03, Amazon $57.99 (Library of Congress Online Catalog).
The latest results of computational verb theory and physical linguistics can be found in book
• 0-9721212-3-4:: T. Yang, Physical Linguistics:measurable linguistics and duality between universe and cognition, Dec. 04, Amazon $77.99 (Library of Congress Online Catalog).
The First Textbook Addressing Computational Verb Controllers
INTRODUCTION TO FUZZY
SETS, FUZZY LOGIC, AND
FUZZY CONTROL SYSTEMS,
Guanrong Chen(CITY UNIVERSITY OF HONG KONG, KOWLOON) and
Trung Tat Pham
(DICENTRAL CORPORATION, HOUSTON, TEXAS, USA), ISBN: 0-8493-1658-8.
Chapter 7: Computational Verb Fuzzy Controllers
• Computational Verbs and Verb Numbers
• Verb Rules and Verb Inference
• Computational Verb-Based Fuzzy PID Controllers
See details in the flyer.
