By Jan-Olof Eklundh (auth.), Dr. J. K. Aggarwal (eds.)
This quantity comprises revised papers in keeping with contributions to the NATO complicated learn Workshop on Multisensor Fusion for machine imaginative and prescient, held in Grenoble, France, in June 1989. The 24 papers awarded right here hide a wide diversity of subject matters, together with the foundations and concerns in multisensor fusion, details fusion for navigation, multisensor fusion for item reputation, community techniques to multisensor fusion, desktop architectures for multi sensor fusion, and purposes of multisensor fusion. The individuals met within the appealing atmosphere of Mont Belledonne in Grenoble to debate their present paintings in a atmosphere conducive to interplay and the trade of rules. each one player is a well-known chief in his or her zone within the educational, governmental, or commercial study group. The workshop all for options for the fusion or integration of sensor details to accomplish the optimal interpretation of a scene. numerous members provided novel issues of view at the integration of data. The 24 papers provided during this quantity are in keeping with these amassed by means of the editor after the workshop, and mirror a number of facets of our discussions. The papers are geared up into 5 elements, as follows.
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The differences of local mean and SD are used for segmentation. The statistical approach is also applicable to range and velocity data. For example, the average range value for a segment is a good estimator of its distance to the sensor. 2 Thermal Image Characteristics and Segmentation The pixel values in thermal (infrared or IR) images are usually dominated by the thermal properties of different materials, such as the thermal capacitance and the heat sink/source distinction. Some of these properties can differentiate object surface materials and, hence, indicate the existence of MMOs.
35 [Fau86] Faugeras, O. D. , N. Ayache, and B. , April, 1986. [For82] Forgy, C. L. , "RETE: A Fast Algorithm for the Many Pattern Many Object Pattern Match Problem", Artificial Intelligence, 19(1), Sept. 1982. [Gen82] Gennery, D. , "Tracking Known Three Dimensional Objects", Proc. of the National Conference on Artificial Intelligence (AAAI-82), Pittsburgh, 1982. , "A Blackboard Architecture for Control", Artificial Intelligence, Vol 26, 1985. [Her86] Herman M. and Kanade T. Incremental reconstruction of 3D scenes from multiple complex images.
In this section we briefly discuss this idea. The symbolic analog for a vector of parameters is an association of properties. Such data structures are very widely used in computer science. Such an implementation is particularly straightforward using a "schema" or frames representation. The problem of representing the uncertainty of each property can be handled by an of several AI techniques. For example, each property can contain contain a list of legal values. The current value of the property can be a list of possible values from the list legal values.
