U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Https

Secure .gov websites use HTTPS
A lock () or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Breadcrumb

  1. Home

SHREC'09 Track: Generic Shape Retrieval

The objectives of this shape retrieval contest are to evaluate the performance of 3D shape retrieval approaches on a new generic 3D shape benchmark.

Task description: In 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.

Data set: In this new generic benchmark there are 800 3D models. The target database 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).

Evaluation Methodology: We will employ the following evaluation measures: Precision-Recall curve; Average Precision (AP) and Mean Average Precision (MAP); E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2).

Paper: Godil, A., Dutagaci, H., Akgül, C.B., Axenopoulos, A., Bustos, B., Chaouch, M., Daras, P., Furuya, T., Kreft, S., Lian, Z. and Napoleon, T., 2009, March. SHREC'09 Track: Generic shape retrieval. In 3DOR (pp. 61-68). http://dx.doi.org/10.2312/3DOR/3DOR09/061-068

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2009-02-02 00:00:00
Date Created: N/A
Views:
Data Provided by:
3D Shape Retrieval
Dataset Owner: N/A

Access this data

Contact dataset owner Landing Page URL
Download URL
Table representation of structured data
Title SHREC'09 Track: Generic Shape Retrieval
Description The objectives of this shape retrieval contest are to evaluate the performance of 3D shape retrieval approaches on a new generic 3D shape benchmark. Task description: In 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. Data set: In this new generic benchmark there are 800 3D models. The target database 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). Evaluation Methodology: We will employ the following evaluation measures: Precision-Recall curve; Average Precision (AP) and Mean Average Precision (MAP); E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2). Paper: Godil, A., Dutagaci, H., Akgül, C.B., Axenopoulos, A., Bustos, B., Chaouch, M., Daras, P., Furuya, T., Kreft, S., Lian, Z. and Napoleon, T., 2009, March. SHREC'09 Track: Generic shape retrieval. In 3DOR (pp. 61-68). http://dx.doi.org/10.2312/3DOR/3DOR09/061-068
Modified 2009-02-02 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:afzal.godil@nist.gov
Keywords 3D Shape Retrieval , 3D Models , Generic Shape Retrieval , Evaluation
{
    "identifier": "ark:\/88434\/mds2-2211",
    "accessLevel": "public",
    "references": [
        "http:\/\/dx.doi.org\/10.2312\/3DOR\/3DOR09\/069-076"
    ],
    "contactPoint": {
        "hasEmail": "mailto:afzal.godil@nist.gov",
        "fn": "Afzal A. Godil"
    },
    "programCode": [
        "006:045"
    ],
    "@type": "dcat:Dataset",
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-2211",
    "description": "The objectives of this shape retrieval contest are to evaluate the performance of 3D shape retrieval approaches on a new generic 3D shape benchmark.\n\nTask description: In 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.\n\nData set: In this new generic benchmark there are 800 3D models. The target database 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).\n\nEvaluation Methodology: We will employ the following evaluation measures: Precision-Recall curve; Average Precision (AP) and Mean Average Precision (MAP); E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2).\n\nPaper: Godil, A., Dutagaci, H., Akg\u00fcl, C.B., Axenopoulos, A., Bustos, B., Chaouch, M., Daras, P., Furuya, T., Kreft, S., Lian, Z. and Napoleon, T., 2009, March. SHREC'09 Track: Generic shape retrieval. In 3DOR (pp. 61-68). http:\/\/dx.doi.org\/10.2312\/3DOR\/3DOR09\/061-068",
    "language": [
        "en"
    ],
    "title": "SHREC'09 Track: Generic Shape Retrieval",
    "distribution": [
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2211\/SHREC2009_Generic.zip.sha256",
            "mediaType": "text\/plain",
            "title": "SHA256 File for SHREC'09 Track: Generic shape retrieval"
        },
        {
            "accessURL": "https:\/\/doi.org\/10.18434\/M32211",
            "title": "DOI Access for SHREC'09 Track: Generic Shape Retrieval"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2211\/SHREC2009_Generic.zip",
            "description": "3D models, evaluation code",
            "mediaType": "application\/zip",
            "title": "SHREC'09 Track: Generic shape retrieval"
        }
    ],
    "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": [
        "3D Shape Retrieval",
        "3D Models",
        "Generic Shape Retrieval",
        "Evaluation"
    ]
}

Was this page helpful?