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The notion of subjective image quality (SIQ) is particularly difficult to define as it depends on a large variety of physical attributes and psycho-physical factors. One important attribute which SIQ depends on is the illumination under which visual stimuli are observed. Recent studies have shown that achromatic fidelity (i.e. perceived resemblance in lightness) is significantly less dependent on...
The subjective quality assessment (SQA) is an ever demanding approach due to its in-depth interactivity to the human cognition. The addition of no-reference based scheme could equip the SQA techniques to tackle further challenges. Existing widely used objective metrics-peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) or the subjective estimator-mean opinion score (MOS) requires...
Pedestrian detection is an active problem in computer vision research, with applications in robotics, self-driving cars and surveillance. It involves generating bounding boxes to indicate the location of every pedestrian in an input image. This paper proposes a method to augment a basic pedestrian detector with a Convolutional Neural Network. An implementation of the proposed algorithm was trained...
With the growing of available large datasets for evaluation, face detection in recent literature has progressed rapidly. However, little research has been dedicated to develop a face detector robust to all possible variations. To address this problem, novel unconstrained datasets containing faces with more challenging variations are proposed. We notice that some recent face detectors have not been...
In computational visual attention systems, various feature maps are constructed and integrated to yield the final fixation map. These maps highlight interesting regions within an image that are deemed salient according to some task. According to Ehinger et al. [1], by combining three types of feature maps, the performance is boosted in terms of predicting where human fixate when searching for pedestrians...
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