Electronic Resource
A computational model of visual attention.
| العنوان: | A computational model of visual attention. |
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| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Visual attention is a process by which the Human Visual System (HVS) selects most important information from a scene. Visual attention models are computational or mathematical models developed to predict this information. The performance of the state-of-the-art visual attention models is limited in terms of prediction accuracy and computational complexity. In spite of significant amount of active research in this area, modelling visual attention is still an open research challenge. This thesis proposes a novel computational model of visual attention that achieves higher prediction accuracy with low computational complexity. A new bottom-up visual attention model based on in-focus regions is proposed. To develop the model, an image dataset is created by capturing images with in-focus and out-of-focus regions. The Discrete Cosine Transform (DCT) spectrum of these images is investigated qualitatively and quantitatively to discover the key frequency coefficients that correspond to the in-focus regions. The model detects these key coefficients by formulating a novel relation between the in-focus and out-of-focus regions in the frequency domain. These frequency coefficients are used to detect the salient in-focus regions. The simulation results show that this attention model achieves good prediction accuracy with low complexity. The prediction accuracy of the proposed in-focus visual attention model is further improved by incorporating sensitivity of the HVS towards the image centre and the human faces. Moreover, the computational complexity is further reduced by using Integer Cosine Transform (ICT). The model is parameter tuned using the hill climbing approach to optimise the accuracy. The performance has been analysed qualitatively and quantitatively using two large image datasets with eye tracking fixation ground truth. The results show that the model achieves higher prediction accuracy with a lower computational complexity compared to the state-of-the-art visual atten |
| مصطلحات الفهرس: | Visual saliency, Saliency detection, In focus, DCT, Frequency saliency, Fixation prediction, Attention, Visual attention models, Saliency model, Face saliency |
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| الاتاحة: | Open access content. Open access content |
| ملاحظة: | PDF English |
| Other Numbers: | G5U oai:rgu-repository.worktribe.com:248905 1360473309 |
| المصدر المساهم: | ROBERT GORDON UNIV From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1360473309 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |