{
    "identifier": "ark:\/88434\/mds2-2210",
    "accessLevel": "public",
    "references": [
        "http:\/\/dx.doi.org\/10.2312\/3DOR\/3DOR09\/069-076"
    ],
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Afzal A. Godil"
    },
    "programCode": [
        "006:045"
    ],
    "@type": "dcat:Dataset",
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-2210",
    "description": "There are two objectives of this shape retrieval contest:\n\na) To evaluate partial similarity between query and target objects and retrieve complete 3D models that are relevant to a partial query object.\n\nb) To retrieve 3D models those are relevant to a query depth map. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database.\n\nTask description\n\nIn response to a given set of queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query. The set of queries either consists of partial 3D models or of range images. The participants may present ranked lists for either of the query sets or both. There is no obligation to submit rank lists for both of the query sets.\n\nDataset\n\nThe first query set consists of 20 3D partial models which are obtained by cutting parts from complete models. The objective is to retrieve the models which the query part may belong to. The file format to represent the partial query models is the ASCII Object File Format (*.off).\n\nThis second query set is composed of 20 range images, which are acquired by capturing range data of 20 models from arbitrary view directions. The range images are captured using a desktop 3D scanner. The file format is in the ASCII Object File Format (*.off) representing the scan in a triangular mesh.\n\nThe target database is the same for both of the query sets and it contains 720 complete 3D models, which are categorized into 40 classes. In each class there are 18 models. The file format to represent the 3D models is the ASCII Object File Format (*.off).D Models, Classification files, Evaluation software, Images\n\nPaper: Dutagaci, Helin, Godil, Afzal, et al. \"SHREC'09 track: querying with partial models.\" Proceedings of the 2nd Eurographics conference on 3D Object Retrieval. Eurographics Association, 2009. https:\/\/doi.org\/10.5555\/2381128.2381144",
    "language": [
        "en"
    ],
    "title": "SHREC'09 track: querying with partial models",
    "distribution": [
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2210\/SHREC2009_Partial.zip.sha256",
            "mediaType": "text\/plain",
            "title": "SHA256 File for SHREC 2009 - Shape Retrieval Contest of Partial 3D Models"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2210\/SHREC2009_Partial.zip",
            "description": "Target Set is 3D Models \/ Query Set is partial 3D models \/ Evaluation code",
            "mediaType": "application\/zip",
            "title": "SHREC 2009 - Shape Retrieval Contest of Partial 3D Models"
        },
        {
            "accessURL": "https:\/\/doi.org\/10.18434\/M32210",
            "title": "DOI Access for SHREC'09 track: querying with partial models"
        }
    ],
    "license": "https:\/\/www.nist.gov\/open\/license",
    "bureauCode": [
        "006:55"
    ],
    "modified": "2009-02-02 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "accrualPeriodicity": "irregular",
    "theme": [
        "Information Technology:Data and informatics",
        "Mathematics and Statistics:Image and signal processing"
    ],
    "issued": "2020-04-22",
    "keyword": [
        "Information Search and Retrieval",
        "3D Shape Retrieval",
        "Partial 3D Models"
    ]
}