Fahad Fazal Elahi Guraya

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A video sequence is more than a sequence of still images. It contains a strong spatial–temporal correlation between the regions of consecutive frames. The most important characteristic of videos is the perceived motion foreground objects across the frames. The motion of foreground objects dramatically changes the importance of the objects in a scene and(More)
—When viewing video sequences, the human visual system (HVS) tends to focus on the active objects. These are perceived as the most salient regions in the scene. Additionally, human observers tend to predict the future positions of moving objects in a dynamic scene and to direct their gaze to these positions. In this paper we propose a saliency detection(More)
Human visual system is very fast at detectingsalient information of a scene. This detection mechanism ishardwired into our HVS. In many applications there is aneed to find a robust visual saliency detection method thatmimics this detection mechanism in the human visual system.Several saliency models are proposed in the literature mostof them ignore the(More)
In this paper we study image distortions and impairments that affect the perceived quality of blackboard lectures images. We also propose a novel reference free image quality evaluation metric that correlates well with the perceived image quality. The perceived quality of images of blackboard lecture contents is mostly affected by the presence of noise,(More)
The perception of video is different from that of image because of the motion information in video. Motion objects lead to the difference between two neighboring frames which is usually focused on. By far, most papers have contributed to image saliency but seldom to video saliency. Based on scene understanding, a new video saliency detection model with(More)
Visual saliency models(VSM) mimic the human visual system to distinguish the salient regions from the non-salient ones in an image or video. Most of the visual saliency model in the literature are static hence they can only be used for images. Motion is important information in case of videos that is not present in still images and thus not used in most of(More)
The Human Visual System (HVS) tends to focus on specific regions of viewed images or video frames, this is done effortlessly, instantly and unconsciously. These are called salient regions and form a saliency map, which could be used to improve a number of image and video processing techniques. In this paper, we propose a novel non-reference objective video(More)
Visual attention models (VAM) try to mimic the human visual system in distinguishing salient regions from non-salient ones in the scene. Only a few attention models propose to detect salient motion in surveillance videos. These model utilizes static features such as color, intensity, orientation, face, and dynamic features such as motion to detect most(More)
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