1 January 1998 Recognition of 3D tree crown structure based on its pictures: statistical approach
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Proceedings Volume 3345, International Workshop on New Approaches to High-Tech Materials: Nondestructive Testing and Computer Simulations in Materials Science and Engineering; (1998); doi: 10.1117/12.299615
Event: International Workshop on New Approaches to High Tech Materials: Nondestructive Testing and Computer Simulations in Materials Science and Engineering, 1997, St. Petersburg, Russian Federation
Abstract
The investigation is devoted to the recognition of 3D object structure on the basis of the object pictures. Recognition problem is solved as statistical one, since the nature of the structures are stochastic most likely. In its turn the images are damaged with noise. Any structure under recognition is assumed to be a trajectory of a stochastic markovian process. A priori necessary information is the set of the values of the markovian process parameters to determine uniquely the general population of all structures for current recognition session. The significance level as input parameter serves to recognize certain domain of the general population the recognized structure matches with prescribed probability. Our method (algorithm and software) could gain wide-spread acceptance in object visual control, ecology monitoring, as well as to resolve the problem of some alive object growth description, i.e. plants and trees growth.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexei A. Ivankov, Mikhail A. Kurochkin, "Recognition of 3D tree crown structure based on its pictures: statistical approach", Proc. SPIE 3345, International Workshop on New Approaches to High-Tech Materials: Nondestructive Testing and Computer Simulations in Materials Science and Engineering, (1 January 1998); doi: 10.1117/12.299615; https://doi.org/10.1117/12.299615
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KEYWORDS
Stochastic processes

3D modeling

3D image processing

Statistical analysis

Detection and tracking algorithms

Ecology

Object recognition

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