| Data: |
2015 |
| Resum: |
The goal of my PhD was to propose an efficient approach for emotional impact recognition based on CBIR techniques (descriptors, image representation). The main idea relies in classifying images according to their emotion which can be "Negative", "Neutral" or "Positive". Emotion is related to the image content and also to the personal feelings. To achieve our goal we firstly need a correct assessed image database. Our first contribution is about this aspect. We proposed a set of 350 diversifed images rated by people around the world. Added to our choice to use CBIR methods, we studied the impact of visual saliency for the subjective evaluations and interest region segmentation for classification. The results are really interesting and prove that the CBIR methods are useful for emotion recognition. The chosen desciptors are complementary and their performance is consistent on the database we have built and on IAPS, reference database for the analysis of the image emotional impact. |
| Nota: |
Advisors: François Lecellier and Christine Fernandez-Maloigne. PhD thesis defended 3rd October 2013, University of Bristol |
| Drets: |
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.  |
| Llengua: |
Anglès |
| Document: |
Altres ; recerca ; Versió publicada |
| Matèria: |
Computer vision ;
Features and image descriptors ;
Other applications |
| Publicat a: |
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 14 Núm. 3 (2015) , p. 36-38 (Special Issue on Recent PhD Thesis Dissemination (2014)) , ISSN 1577-5097 |
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