A knowledge-based machine vision system for space station automation

A simple knowledge-based approach to the recognition of objects in man-made scenes is being developed. Specifically, the system under development is a proposed enhancement to a robot arm for use in the space station laboratory module. The system will take a request from a user to find a specific object, and locate that object by using its camera input and information from a knowledge base describing the scene layout and attributes of the object types included in the scene. In order to use realistic test images in developing the system, researchers are using photographs of actual NASA simulator panels, which provide similar types of scenes to those expected in the space station environment. Figure 1 shows one of these photographs. In traditional approaches to image analysis, the image is transformed step by step into a symbolic representation of the scene. Often the first steps of the transformation are done without any reference to knowledge of the scene or objects. Segmentation of an image into regions generally produces a counterintuitive result in which regions do not correspond to objects in the image. After segmentation, a merging procedure attempts to group regions into meaningful units that will more nearly correspond to objects. Here, researchers avoid segmenting the image as a whole, and instead use a knowledge-directed approach to locate objects in the scene. The knowledge-based approach to scene analysis is described and the categories of knowledge used in the system are discussed

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Thesis (M.A.)--Boston University This item was digitized by the Internet Archive

Multiscale Discriminant Saliency for Visual Attention

The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio

Mapping the Structure and Function of the E1 and E2 Glycoproteins in Alphaviruses

The 9 Å resolution cryo-electron microscopy map of Sindbis virus presented here provides structural information on the polypeptide topology of the E2 protein, on the interactions between the E1 and E2 glycoproteins in the formation of a heterodimer, on the difference in conformation of the two types of trimeric spikes, on the interaction between the transmembrane helices of the E1 and E2 proteins, and on the conformational changes that occur when fusing with a host cell. The positions of various markers on the E2 protein established the approximate topology of the E2 structure. The largest conformational differences between the icosahedral surface spikes at icosahedral 3-fold and quasi-3-fold positions are associated with the monomers closest to the 5-fold axes. The long E2 monomers, containing the cell receptor recognition motif at their extremities, are shown to rotate by about 180^o and to move away from the center of the spikes during fusion

Land cover classification using multi-temporal MERIS vegetation indices

The spectral, spatial, and temporal resolutions of Envisat's Medium Resolution Imaging Spectrometer (MERIS) data are attractive for regional- to global-scale land cover mapping. Moreover, two novel and operational vegetation indices derived from MERIS data have considerable potential as discriminating variables in land cover classification. Here, the potential of these two vegetation indices (the MERIS global vegetation index (MGVI), MERIS terrestrial chlorophyll index (MTCI)) was evaluated for mapping eleven broad land cover classes in Wisconsin. Data acquired in the high and low chlorophyll seasons were used to increase inter-class separability. The two vegetation indices provided a higher degree of inter-class separability than data acquired in many of the individual MERIS spectral wavebands. The most accurate landcover map (73.2%) was derived from a classification of vegetation index-derived data with a support vector machine (SVM), and was more accurate than the corresponding map derived from a classification using the data acquired in the original spectral wavebands

Visualization of membrane protein domains by cryo-electron microscopy of dengue virus

Improved technology for reconstructing cryo-electron microscopy (cryo-EM) images has now made it possible to determine secondary structural features of membrane proteins in enveloped viruses. The structure of mature dengue virus particles was determined to a resolution of 9.5 Å by cryo-EM and image reconstruction techniques, establishing the secondary structural disposition of the 180 envelope (E) and 180 membrane (M) proteins in the lipid envelope. The ɑ-helical 'stem' regions of the E molecules, as well as part of the N-terminal section of the M proteins, are buried in the outer leaflet of the viral membrane. The 'anchor' regions of E and the M proteins each form antiparallel E-E and M-M transmembrane alpha-helices, leaving their C termini on the exterior of the viral membrane, consistent with the predicted topology of the unprocessed polyprotein. This is one of only a few determinations of the disposition of transmembrane proteins in situ and shows that the nucleocapsid core and envelope proteins do not have a direct interaction in the mature virus