Conference paper Open Access

Query and Keyframe Representations for Ad-hoc Video Search

Markatopoulou, Foteini; Galanopoulos, Damianos; Mezaris, Vasileios; Patras, Ioannis


JSON Export

{
  "files": [
    {
      "links": {
        "self": "https://zenodo.org/api/files/d42eb24d-f66c-410e-b53e-65210a4ceb3a/icmr17_1_preprint.pdf"
      }, 
      "checksum": "md5:2b78b66b9f9e9b178be9ae8d9f58654a", 
      "bucket": "d42eb24d-f66c-410e-b53e-65210a4ceb3a", 
      "key": "icmr17_1_preprint.pdf", 
      "type": "pdf", 
      "size": 777023
    }
  ], 
  "owners": [
    26037
  ], 
  "doi": "10.1145/3078971.3079041", 
  "stats": {
    "version_unique_downloads": 103.0, 
    "unique_views": 176.0, 
    "views": 183.0, 
    "version_views": 183.0, 
    "unique_downloads": 103.0, 
    "version_unique_views": 176.0, 
    "volume": 80033369.0, 
    "version_downloads": 103.0, 
    "downloads": 103.0, 
    "version_volume": 80033369.0
  }, 
  "links": {
    "doi": "https://doi.org/10.1145/3078971.3079041", 
    "latest_html": "https://zenodo.org/record/809672", 
    "bucket": "https://zenodo.org/api/files/d42eb24d-f66c-410e-b53e-65210a4ceb3a", 
    "badge": "https://zenodo.org/badge/doi/10.1145/3078971.3079041.svg", 
    "html": "https://zenodo.org/record/809672", 
    "latest": "https://zenodo.org/api/records/809672"
  }, 
  "created": "2017-06-16T08:02:18.695592+00:00", 
  "updated": "2020-01-20T17:36:30.828570+00:00", 
  "conceptrecid": "809671", 
  "revision": 8, 
  "id": 809672, 
  "metadata": {
    "access_right_category": "success", 
    "doi": "10.1145/3078971.3079041", 
    "description": "<p>This paper presents a fully-automatic method that combines video concept detection and textual query analysis in order to solve the problem of ad-hoc video search. We present a set of NLP steps that cleverly analyse different parts of the query in order to convert it to related semantic concepts, we propose a new method for transforming concept-based keyframe and query representations into a common semantic embedding space, and we show that our proposed combination of concept-based representations with their corresponding semantic embeddings results to improved video search accuracy. Our experiments in the TRECVID AVS 2016 and the Video Search 2008 datasets show the effectiveness of the proposed method compared to other similar approaches.</p>", 
    "license": {
      "id": "CC-BY-4.0"
    }, 
    "title": "Query and Keyframe Representations for Ad-hoc Video Search", 
    "relations": {
      "version": [
        {
          "count": 1, 
          "index": 0, 
          "parent": {
            "pid_type": "recid", 
            "pid_value": "809671"
          }, 
          "is_last": true, 
          "last_child": {
            "pid_type": "recid", 
            "pid_value": "809672"
          }
        }
      ]
    }, 
    "communities": [
      {
        "id": "invid-h2020"
      }, 
      {
        "id": "moving-h2020"
      }
    ], 
    "grants": [
      {
        "code": "693092", 
        "links": {
          "self": "https://zenodo.org/api/grants/10.13039/501100000780::693092"
        }, 
        "title": "Training towards a society of data-savvy information professionals to enable open leadership innovation", 
        "acronym": "MOVING", 
        "program": "H2020", 
        "funder": {
          "doi": "10.13039/501100000780", 
          "acronyms": [], 
          "name": "European Commission", 
          "links": {
            "self": "https://zenodo.org/api/funders/10.13039/501100000780"
          }
        }
      }, 
      {
        "code": "687786", 
        "links": {
          "self": "https://zenodo.org/api/grants/10.13039/501100000780::687786"
        }, 
        "title": "In Video Veritas \u2013 Verification of Social Media Video Content for the News Industry", 
        "acronym": "InVID", 
        "program": "H2020", 
        "funder": {
          "doi": "10.13039/501100000780", 
          "acronyms": [], 
          "name": "European Commission", 
          "links": {
            "self": "https://zenodo.org/api/funders/10.13039/501100000780"
          }
        }
      }
    ], 
    "keywords": [
      "Video search", 
      "Zero-shot learning", 
      "Visual analysis"
    ], 
    "publication_date": "2017-06-08", 
    "creators": [
      {
        "affiliation": "Information Technologies Institute (ITI) - Centre for Research and Technology Hellas (CERTH)", 
        "name": "Markatopoulou, Foteini"
      }, 
      {
        "affiliation": "Information Technologies Institute (ITI) - Centre for Research and Technology Hellas (CERTH)", 
        "name": "Galanopoulos, Damianos"
      }, 
      {
        "affiliation": "Information Technologies Institute (ITI) - Centre for Research and Technology Hellas (CERTH)", 
        "name": "Mezaris, Vasileios"
      }, 
      {
        "affiliation": "Queen Mary University of London", 
        "name": "Patras, Ioannis"
      }
    ], 
    "meeting": {
      "acronym": "ICMR 2017", 
      "url": "http://icmr2017.ro/index.php", 
      "dates": "6-9 June 2017", 
      "place": "Bucharest, Romania", 
      "title": "ACM International Conference on Multimedia Retrieval 2017"
    }, 
    "access_right": "open", 
    "resource_type": {
      "subtype": "conferencepaper", 
      "type": "publication", 
      "title": "Conference paper"
    }
  }
}
183
103
views
downloads
Views 183
Downloads 103
Data volume 80.0 MB
Unique views 176
Unique downloads 103

Share

Cite as