September 25, 2016 Conference paper Open Access

Christos Tzelepis; Eftichia Mavridaki; Vasileios Mezaris; Ioannis Patras

JSON-LD (schema.org) Export

{
  "description": "<p>In this paper we propose a video aesthetic quality assessment method that combines the representation of each video according to a set of photographic and cinematographic rules, with the use of a learning method that takes the video representation's uncertainty into consideration. Specifically, our method exploits the information derived from both low- and high-level analysis of video layout, leading to a photo- and motion-based video representation scheme. Subsequently, a kernel Support Vector Machine (SVM) extension, the KSVM-iGSU, is trained to classify the videos and retrieve those of high aesthetic value. Experimental results on our large dataset verify the effectiveness of the proposed method. We also make publicly available our dataset, in order to facilitate research in the area of video aesthetic quality assessment.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Information Technologies Institute (ITI), CERTH, Queen Mary University of London", 
      "@type": "Person", 
      "name": "Christos Tzelepis"
    }, 
    {
      "affiliation": "Information Technologies Institute (ITI), CERTH", 
      "@type": "Person", 
      "name": "Eftichia Mavridaki"
    }, 
    {
      "affiliation": "Information Technologies Institute (ITI), CERTH", 
      "@type": "Person", 
      "name": "Vasileios Mezaris"
    }, 
    {
      "affiliation": "Queen Mary University of London", 
      "@type": "Person", 
      "name": "Ioannis Patras"
    }
  ], 
  "headline": "VIDEO AESTHETIC QUALITY ASSESSMENT USING KERNEL SUPPORT VECTOR MACHINE WITH ISOTROPIC GAUSSIAN SAMPLE UNCERTAINTY (KSVM-IGSU)", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2016-09-25", 
  "url": "https://zenodo.org/record/159236", 
  "keywords": [
    "Video aesthetic quality assessment", 
    "Rules of photography and cinematography", 
    "Support vector machine", 
    "Video representation uncertainty"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1109/ICIP.2016.7532791", 
  "@id": "https://doi.org/10.1109/ICIP.2016.7532791", 
  "@type": "ScholarlyArticle", 
  "name": "VIDEO AESTHETIC QUALITY ASSESSMENT USING KERNEL SUPPORT VECTOR MACHINE WITH ISOTROPIC GAUSSIAN SAMPLE UNCERTAINTY (KSVM-IGSU)"
}