Huntsberger, T. L. (1990): Comparison of Techniques for Disparate Sensor Fu- sion. In: Proc. SPIE Syrup. Sensor Fusion III: 3-D Perception and Recognition 1383, Boston, MA, 589-595  Home/Search   Document Not in Database   Summary   Related Articles   Check

....to the vertical, diagonal, and horizontal detail channels are shown in clockwise order from the upper right hand corner of the figure, and at different levels of resolution while traveling from the lower right to the upper left corner. Fuzzy Self Organizing Feature Map The neural network model [21] used for the action generation process is a modification of the self organizing feature maps of Kohonen [22] It is also a member of the generalized class of clustering networks developed by Pal, Bezdek, and Tsao [23] hereafter referred to as GLVQ) The FSOFM, shown in Fig. 4, consists of three ....

Huntsberger, T. L. (1990): Comparison of Techniques for Disparate Sensor Fu- sion. In: Proc. SPIE Syrup. Sensor Fusion III: 3-D Perception and Recognition 1383, Boston, MA, 589-595

.... bats [28] The optic tectum in the rattlesnake directly integrates bimodal inputs (visual and thermal infrared) in a set of six specialized neurons [21] Our previous studies have indicated that these neuronal types can be used as generalized fusion filters for any pair of disparate sensory inputs [11, 12, 13]. 1 Chapter 11 Bimodal Neurons and Networks Page 2 Aside from the fact that design features in this system may be directly applicable to the engineering problem of integrating visual and infrared stimuli, another reason for selecting this particular system is that it is more accessible than ....

T. L. Huntsberger. Comparison of techniques for disparate sensor fusion. In Proc. SPIE Sympos. on Sensor Fusion III: 3--D Perception and Recognition, volume 1383, pages 589--594, Boston, MA, November 1990.

....Intelligent Systems Laboratory, Department of Computer Science University of South Carolina, Columbia, SC 29208 Abstract. 1 Introduction Early research in computer vision was concerned mainly with static images. Our previous work concentrated on analysis of static images for segmentation purposes [1,24]. The method used a fuzzy self organizing feature map (FSOFM) 31] as part of a multistage neural network modeled after the rattlesnake optic tectum for the fusion of two sensory modalities [1] Results comparable to and better than traditional evidence combination schemes were obtained [24] For ....

.... [1,24] The method used a fuzzy self organizing feature map (FSOFM) 31] as part of a multistage neural network modeled after the rattlesnake optic tectum for the fusion of two sensory modalities [1] Results comparable to and better than traditional evidence combination schemes were obtained [24]. For some applications, the analysis of static images may su er from inherent limitations in the amount of three dimensional information that can be extracted. Recently, dynamic scene analysis in the machine vision eld has been given increasing attention [4,37,56] and references therein) The ....

Huntsberger, T. L. (1990). Comparison of techniques for disparate sensor fusion. In Proc. SPIE Sympos. Sensor Fusion III: 3-D Perception and Recognition, Volume 1383, Boston, MA, pp. 589-595.

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