Three-dimensional visualization environment for multisensor data analysis, interpretation, and model-based object recognition

نویسندگان

  • Michael E. Goss
  • J. Ross Beveridge
  • Mark R. Stevens
  • Aaron D. Fuegi
چکیده

Model-based object recognition must solve three-dimensional geometric problems involving the registration of multiple sensors and the spatial relationship of a three-dimensional model to the sensors. Observation and verification of the registration and recognition processes requires display of these geometric relationships. We have developed a prototype software system which allows a user to interact with the sensor data and model matching system in a three-dimensional environment. This visualization environment combines range imagery, color imagery, thermal (infrared) imagery, and CAD models of objects to be recognized. We are currently using imagery of vehicles travelling off-road (a challenging environment for the object recognizer). Range imagery is used to create a partial three-dimensional representation of a scene. Optical imagery is mapped onto this partial 3D representation. Visualization allows monitoring of the recognizer as it solves for the type and position of the object. The object is rendered from its associated CAD model. In addition to its usefulness in development of the object recognizer, we foresee eventual use of this technology in a fielded system for operator verification of automatic target recognition results.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Urban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data

Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...

متن کامل

Space as a Semiotic Object: A Three-Dimensional Model of Vertical Structure of Space in Calvino’s Invisible Cities

Following the “spatial turn” of the last 3 decades in humanities and social sciences and the structure of semiotic object, this research studies space as the main semiotic object of Calvino’s (1972) Invisible Cities. Significance of this application resides in examining the possibility of providing a more concrete methodology based on the integration of Zoran’s (1984) 3 vertical levels of const...

متن کامل

Multisensor data fusion for automated scene interpretation

An approach to the combined extraction of linear as well as two-dimensional objects from multisensor data based on a feature-and object-level fusion of the results is proposed. The data sources are DAIS hyperspectral data, AES-1 SAR data, and high-resolution panchromatic digital orthoimages. Rural test areas consisting of a road network, agricultural elds, and small villages were investigated. ...

متن کامل

Visualizing Multisensor Model-Based Object Recognition

A di cult problem when designing automatic object recognition algorithms is the visualiza tion of relationships between sensor data and the internal models used by the recognition al gorithms In our particular case we need to coregister color thermal infrared and range imagery to D object models in an e ort to determine object positions and orientations in three space In this paper we describe ...

متن کامل

RSTA Research of the Colorado State, University of Massachusetts and Alliant Techsystems Team

The complementary nature of LADAR, FLIR and color data for ATR is being exploited by new algorithms in a three stage recognition system. The stages are initial detection, target class and pose hypothesis generation, and precise model to multisensor coregistra-tion matching. Coregistration globally aligns 3D target models with range, IR and color imagery while simultaneously reening registration...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995