21 research outputs found

    Metadata for all: Descriptive standards and metadata sharing across libraries, archives and museums

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    Integrating digital content from libraries, archives and museums represents a persistent challenge. While the history of standards development is rife with examples of cross-community experimentation, in the end, libraries, archives and museums have developed parallel descriptive strategies for cataloguing the materials in their custody. Applying in particular data content standards by material type, and not by community affiliation, could lead to greater data interoperability within the cultural heritage community. In making this argument, the article demystifies metadata by defining and categorizing types of standards, provides a brief historical overview of the rise of descriptive standards in museums, libraries and archives, and considers the current tensions and ambitions in making descriptive practice more economic [1]

    LiDAR-guided object search and detection in Subterranean Environments

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    Detecting objects of interest, such as human survivors, safety equipment, and structure access points, is critical to any search-and-rescue operation. Robots deployed for such time-sensitive efforts rely on their onboard sensors to perform their designated tasks. However, as disaster response operations are predominantly conducted under perceptually degraded conditions, commonly utilized sensors such as visual cameras and LiDARs suffer in terms of performance degradation. In response, this work presents a method that utilizes the complementary nature of vision and depth sensors to leverage multi-modal information to aid object detection at longer distances. In particular, depth and intensity values from sparse LiDAR returns are used to generate proposals for objects present in the environment. These proposals are then utilized by a Pan-Tilt-Zoom (PTZ) camera system to perform a directed search by adjusting its pose and zoom level for performing object detection and classification in difficult environments. The proposed work has been thoroughly verified using an ANYmal quadruped robot in underground settings and on datasets collected during the DARPA Subterranean Challenge finals
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