Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 12 of 12 for “"Saliency detection"”.
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Saliency detection via divergence analysis: a unified perspective
… We present a unified view of various bottom-up saliency detection algorithms. As these methods were proposed from intuition and principles inspired from psychophysical studies of human vision, the theoretical relations among them are unclear. In this thesis, we provide such a bridge. The …
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Visual Saliency Detection and its Application to Image Retrieval
… work. In the following two novel approaches to saliency detection are presented. In comparison to previous works in this field the proposed approaches tackles saliency estimation on the object-wise level. In addition, one of the proposed approach solves saliency detection problem through …
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Image Co-saliency Detection and Co-segmentation from The Perspective of Commonalities
Image co-saliency detection and image co-segmentation aim to identify the common salient objects and extract them in a group of images. Image co-saliency detection and image co-segmentation are important for many content-based applications such as image retrieval, image editing, and content aware …
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Visual saliency computation for image analysis
Visual saliency computation is about detecting and understanding salient regions and elements in a visual scene. Algorithms for visual saliency computation can give clues to where people will look in images, what objects are visually prominent in a scene, etc. Such algorithms could be useful in a …
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Cognitive feature fusion for effective pattern recognition in multi-modal images and videos
Image retrieval and object detection have been always popular topics in computer vision, wherein feature extraction and analysis plays an important role. Effective feature descriptors can represent the characteristics of the images and videos, however, for various images and videos, single feature …
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A Study on Deep Learning: Training, Models and Applications
… third proposed method is to apply CNNs to image saliency detection. In this approach, a gradient descent method is used to iteratively modify the input images based on pixel-wise gradients to reduce a pre-defined cost function. Moreover, SLIC superpixels and low level saliency features are …
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Saliency in audio and visual signals
This dissertation studies saliency and its applications in audio and visual signals. For each portion of the signal, its saliency means the likelihood of attracting bottom-up attention in the perception process. In computer vision, image saliency is described by local contrasts of features. Each …
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The parallel nature of early visual processing in visual search
… In contrast to the pre-attentive process of saliency detection and generation proposed by classic theories, Target Contrast Signal Theory proposes that parallel processing in early vision involves an evidence accumulation process that is aimed at rejecting items as non-targets. In this …
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Superpixel Segmentation Systems: Design and Analysis
… merging for image segmentation, object tracking, detection, depth estimation, object recognition, image denoising, object-based compression, video processing, video coding, saliency detection, and deep learning. We present a four-way experimental evaluation of the effectiveness of measures used to …
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Robust graph transduction
… framework proposed in Chapter 4 to accomplish saliency detection, so that the saliency values of all the superpixels are decided from simple superpixels to more difficult ones. The difficulty of a superpixel is judged by its informativity, individuality, inhomogeneity, and connectivity. As a …
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A computational model of visual attention.
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 …