image saliency IEEE PAPER
In computer vision, a saliency map is an image that shows each pixel's unique quality. The goal of a saliency map is to simplify and/or change the representation
Saliency modeling from image histograms
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We proposed a computational visual saliency modeling technique. The proposed technique makes use of a color co-occurrence histogram (CCH) that captures not onlyhow manybut alsowhere and howimage pixels are composed into a visually perceivable image. Hence
Saliency, scale and image description
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Many computer vision problems can be considered to consist of two main tasks: the extraction of image content descriptions and their subsequent matching. The appropriate choice of type and level of description is of course task dependent, yet it is generally Image quality assessment (IQA) is a critical issue in image processing applications, but traditional criteria based on the differences between reference and distorted images do not correlate well with perceived quality. MSSIM and VIF criteria proposed recently are regarded
Semantics-based image retrieval by region saliency
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Abstract. We propose a new approach for semantics-based image retrieval. We use color- texture classification to generate the codebook which is used to segment images into regions. The content of a region is characterized by its self-saliency and the lower-level
Saliency-driven scaling optimization for image retargeting
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Abstract This paper proposes a saliency-weighted scaling factor energy for image retargeting. Considering that salient objects should be scaled with a larger scaling factor with respect to nonsalient regions, we define a quadric energy to establish the relation Abstract Many computer vision applications, such as object recognition and content-based image retrieval could function more reliably and effectively if regions of interest were isolated from their background. A new method for regions of interest extraction from color image
Saliency-Driven Image Acuity Modulation on a Reconfigurable Array of Spiking Silicon Neurons
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Abstract We have constructed a system that uses an array of 9,600 spiking silicon neurons, a fast microcontroller, and digital memory, to implement a reconfigurable network of integrate- and-fire neurons. The system is designed for rapid prototyping of spiking neural networks
Self-organizing map-based color image segmentation with k-means clustering and saliency map
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Natural image segmentation is an important topic in digital image processing, and it could be solved by clustering methods. We present in this paper an SOM-based k-means method (SOM-K) and a further saliency map-enhanced SOM-K method (SOM-KS). In SOM-K, pixel
Real-time Enhancement of Image and Video Saliency using Semantic Depth of Field.
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Abstract: In this paper, we propose a method for automatically directing viewers visual attention to important regions of images and videos in low-level vision. Inspired by the modern model of visual attention, the importance map of an input scene is automatically
Learning Hierarchical Image Representation with Sparsity, Saliency and Locality.
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Abstract This paper presents a deep learning model of building up hierarchical image representation. Each layer of this hierarchy consists of three components: sparse coding, saliency pooling and local grouping. With sparse coding we identify distinctive coefficients
Saliency, scale and image description
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Abstract Many computer vision problems can be considered to consist of two main tasks: the extraction of image content descriptions and their subsequent matching. The appropriate choice of type and level of description is of course task dependent, yet it is generally
Utilizing saliency operators for image matching
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Abstract A novel concept of using saliency operators for matching tasks is introduced. The proposed method detects large salient regions in an image by a saliency operator recently proposed by Kadir and Brady. Within these salient regions we use small salient regions (sub-
An image-based approach for automatic detecting tasseling stage of maize using spatio-temporal saliency
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ABSTRACT In this paper, we explored the application of computer vision technology to automatically detect the tasseling stage of maize. The commonly used HOG/SVM detection framework is chosen to recognize the ears of maize for determining the occurrence time of
Image based Monument Recognition using Graph based Visual Saliency
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This article presents an image-based application aiming at simple image classification of well-known monuments in the area of Heraklion, Crete, Greece. This classification takes place by utilizing Graph Based Visual Saliency (GBVS) and employing Scale Invariant
Improving Query Expansion for Image Retrieval via Saliency and Picturability.
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Abstract. In this paper, we present a Wikipedia-based approach to query expansion for the task of image retrieval, by combining salient encyclopaedic concepts with the picturability of words. Our model generates the expanded query terms in a definite two-stage process In this paper, we propose a novel segmentation model integrated the salient regional features into mean shift (MS) clustering segmentation as fusion matrixes. Firstly, a regional visual saliency map of the given image is obtained based on quantification image in HSV
Image Quality Assessment by Saliency Maps.
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Abstract: Image Quality Assessment (IQA) is an interesting challenge for image processing applications. The goal of IQA is to replace human judgement of perceived image quality with a machine evaluation. A large number of methods have been proposed to evaluate the
Image and video region saliency based on space and motion
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Abstract. This paper proposes a new bottom-up paradigm for detecting visual saliency in images and videos, which is based on scale space analysis of the log amplitude spectrum of natural images and videos. A salient region is assumed to be any region exhibiting a distinct
An image saliency detection method by constructing graph model
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Abstract:-In this paper, we present an image saliency detection method by constructing graph model. We extract color, texture and compactness features and segment superpixels from an input image to construct a graph model. Then, saliency for each is measured by
Image retargeting using depth enhanced saliency
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AbstractMost of existing image retargeting approaches only use color information to help preserve important image content. In this paper, we exploit both color and depth information captured by an RGB-D camera to preserve important regions and maintain background
Image Topic Discovery with Saliency Detection.
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Abstract This work proposes a biologically inspired approach to integrate latent topic model with saliency detection. Firstly, a saliency detection algorithm is presented to discriminate salient objects from background parts in the image. A hierarchical latent topic model is
A method of calculating saliency of images and of optimizing efficient distribution of image windows
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Abstract. In this paper, we propose a method of calculating the saliency map of an input image. In this method the saliency gets higher in the areas where the image features are different from those in the surrounding areas and where the features are unfamiliar. We also
Feature coding for image classification based on saliency detection and fuzzy reasoning and its application in elevator videos
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Abstract:-Feature coding is an fundamental step in bag-of-words based model for image classification and have drawn increasing attention in recent works. However, there still exits ambiguity problem, and it is also sensitiveness to unusual features. To improve the stability
On the EEG footprint of image saliency
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Abstract This article investigates the possibility to classify images according to their subjective interest by looking at recorded EEG signals. We classify subjects EEG recordings while they are shown images in a rapid serial visualization (RSVP) task. Our protocol is
Multi-scale saliency search in image analysis.
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Abstract Saliency detection in images is an important outstanding problem both in machine vision design and the understanding of human vision mechanisms. Recently, seminal work by Itti and Koch resulted in an effective saliency-detection algorithm. We reproduce the
A novel approach for automatic image annotation using color saliency
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ABSTRACT: Image annotation task consists to assign a set of semantic tags or labels to a novel image based on some models learned from certain training data. Automatically assigning keywords to images is of great interest as it allows one to index, retrieve, and
APTIVE IMAGE SEGMENTATION BASED ON SALIENCY DETECTION.
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Abstract-in this article, we propose an adaptive image segmentation method based on saliency. First of all, we obtain the saliency map of an image via four bottom-layer feature tunnels, ie color, intensity, direction and energy. The energy tunnel helps to describe the
Headdress Detection Based on Saliency Map for Thangka Portrait Image.
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Abstract This paper applies the saliency map of attention model on Thangka image detection for the first time. Making contrast with some detection methods, an automatic detection algorithm is proposed to segment the headdress area of buddha in Thangka
Shape detection of structural changes in long time-span aerial image samples by new saliency methods
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ABSTRACT: The paper presents a novel, theoretically well-based methodology to find changes in remote sensing image series. The proposed method finds changes in images scanned with a long time-interval difference in very different lighting and surface conditions.
Eye tracking based saliency for automatic content aware image processing
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ABSTRACT Photography provides tangible and visceral mementos of important experiences. Recent research in content-aware image processing to automatically improve photos relies heavily on automatically identifying salient areas in images. While automatic
HIK Based Image Classification Using Saliency Based Multiscale Representation
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AbstractIK based image classification method is proposed which efficiently classifies the images with less background. HIK kernel is used with saliency driven multiscale fusion. The generated scale space in general preserves or even enhances semantically important
Image topic discovery with saliency detection
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Image topic discovery is a challenging task in computer vision, which is important for content understanding, image retrieval, and event detection. In recent years, image categorization by combination of Bagof-Word (BoW) model and latent topic discovery models [1, 2] has
Multiple Structure Based Saliency Detection and Its Application in Image Retrieval
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Abstract. Saliency Detection is a hot research topic in both biological and computer vision. Salient structures, edges, regions would greatly contribute to high-level semantics understanding of peoples attention and improve retrieval precision, object detection, edge
Image-based touristic monument classification using graph based visual saliency and scale-invariant feature transform
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ABSTRACT This paper presents an image-based application using Graph Based Visual Saliency (GBVS) and Scale-Invariant Feature Transform (SIFT), aiming at simple image classification of well-known touristic monuments in the geographic area of Heraklion, Crete,
Review on Image Saliency Detection Algorithms
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AbstractSalient object detection aims at automatically localizing the attractive objects with respect to surrounding background in an image. It can be applied to image browsing, image cropping, image compression, content-based image retrieval etc. Some recent works
SALIENCY BASED ADAPTIVE IMAGE SIGNATURE USING BINARY HOLISTIC IMAGE DESCRIPTOR
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Abstract We introduce a simple image descriptor referred to as the image signature. We show, within the theoretical framework of sparse signal mixing, that this quantity spatially approximates the foreground of an image. We experimentally investigate whether this
Depth of Field Image Segmentation Using Saliency Map and Energy Mapping Techniques
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AbstractImage plays a vital role in image processing. In Image processing Depth of Field is to segment the relevant object from an Image. Depth of Field is the space between the near and extreme objects in a scene. The objective of this work is to segment the image
DETECTION OF IMAGE PAIRS USING CO-SALIENCY MODEL
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Abstract-In this paper a method is presented to identify co-attention objects from an image pair. This method provides an effective way to predict human fixations within multi-images, and robustly highlight co-salient regions. This method generates the SISM by computing
EXPLOITING QUATERNION RARE ORIENTATIONS FOR IMAGE SALIENCY DETECTION
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Abstract. Saliency detection has become lately a valuable tool for many image processing applications. Yet, methodology variations of existing algorithms still permit performances improvement. In this paper a state-of-the-art method, namely phase spectrum of quaternion
AUTOMATED IMAGE RETARGETTING AND CROPPING USING SALIENCY DETECTION AUTOMATIC CONTEXT AWARE CROPPING
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ABSTRACT Image processing is an important field which is enhanced since few decades. One of its essential use in image resizing has received a lot of attention because it is being used in every field of science. Previously, traditional scaling was used to crop the image and
RE-RANKING BASED IMAGE CATEGORIZATION USING SALIENCY DRIVEN NONLINEAR DIFFUSION FILTERING
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ABSTRACT The new technique is proposed for Re-ranking based image categorization using saliency driven nonlinear diffusion filtering. The image categorize based on Re- ranking, using multi-scale information fusion based on the original image. The foreground
Saliency Methods for Object Discovery Based on Image and Depth Segmentation
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Abstract Object discovery is a recent paradigm in computer and robotic vision where the process of interpreting an image starts by proposing a set of candidate regions that potentially correspond to objects; these candidates can be validated later on by object
VISUAL SALIENCY FOR IMAGE CAPTIONING IN NEW MULTIMEDIA SERVICES
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ABSTRACT Image and video captioning are important tasks in visual data analytics, as they concern the capability of describing visual content in natural language. They are the pillars of query answering systems, improve indexing and search and allow a natural form of
IMAGE RETRIEVAL USING GRAPH BASED VISUAL SALIENCY
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Abstract: Saliency methods are recent trends in content based image retrieval usually saliency detection are categorized into bottom-up and top-down approaches. A bottom-up visual saliency model, known as Graph-Based Visual Saliency (GBVS), proposed by
An Automatic Method for Image Matting Based on Saliency Detection
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Abstract Image matting aims at extracting foreground from a given image by means of color and alpha estimation. An automatic matting method based on saliency detection was proposed in this paper, which takes the advantages of saliency detection as prior
Superiority Of Graph-Based Visual Saliency (GVS) Over Other Image Segmentation Methods
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Abstract: Although inherently tedious, the segmentation of images and the evaluation of segmented images are critical in computer vision processes. One of the main challenges in image segmentation evaluation arises from the basic conflict between generality and
Saliency Based Content-Aware Image Retargeting
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Abstract: Imaging technology is increasing very rapidly with the advent and development of digital image processing. Evolution and popularity of Internet and various display devices have further given an additive hand for this enrichment. Different display sizes and different The Industrial Electronics Society is an organization, within the framework of the IEEE, of members with principal professional interest in electronics and electrical sciences as applied to control, treatment, and measurement of industrial processes. All members of the
Image processing using a saliency map for a 49-channel retinal prosthesis
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Purpose: Our second-generation device as a suprachoroidaltransretinal stimulatoin (STS) comprises a 49-channel active electrode array. To achieve effective prosthetic vision using a limited number of electrodes, it is necessary to develop an optimum image processing
Text and Image Retrieval via Saliency Feature and Visual Attention
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Abstract: In the real world applications such as copy protection, fake image detection, landmark search, partial duplicate image retrieval is very needful to any user. Regular users of the internet regularly upload images, photograph which are partially duplicate on the
Image Classification based on Saliency Driven Nonlinear Diffusion and Multi-scale Information Fusion
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Abstract: The saliency driven nonlinear diffusion and multi-scale information fusion preserves or even enhances semantically important structures such as edges, lines, or flow- like structures in the foreground, inhabits and smoothed out the background. Our algorithm
Saliency Based Spatial Partitioning for Global Image Representations
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Abstract. Visual content of the image is the main criterion for measuring image similarity in a content based image retrieval system. A major problem with the existing global image representation models such as Fisher Vectors is the loss of spatial information about the
Determination Of Image Quality Using Saliency Map
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ABSTRACT: Perceptual image quality assessment uses various computation models to measure image quality by considering subjective evaluation. In recent years, according to the psychologists, neurobiologists study has shown that, which areas of image will attract
Visual Saliency in Image Quality Assessment
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Abstract Advances in image quality assessment have shown the benefits of modelling functional components of the human visual system in image quality metrics. Visual saliency, a crucial aspect of the human visual system, is increasingly investigated recently. Current
Visual Saliency-based Theme and Aspect Ratio Preserving Image Cropping for Small Displays
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AbstractScaling to fit an entire image in much smaller display reduces the recognizability of the objects in the image. Therefore, salient portions of an image is cropped and then scaled to fit to a small display. To do so existing methodologies do not maintain the overall
Partial Duplicate Image Retrieval Using Saliency Map
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Abstract With the rapid improvement of Internet and multimedia technology, users regularly generate partial duplicate images for picture sharing, information delivery, and so forth. Unlike in traditional image retrieval, the duplicate regions in partial duplicate images are
Enhanced and Efficient Image Retrieval via Saliency Feature and Visual Attention
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AbstractIn the real world applications such as landmark search, copy protection, fake image detection, partial duplicate image retrieval is very important. In the internet era users regularly upload images which are partially duplicate images on the domains like facebook,
Image Quality Assessment with Saliency Map in Nonsubsampled Contourlet Transform Domain
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Abstract Many researchers evaluate images by objective image quality assessments instead of subjective ones. Objective image quality assessment sets up mathematical model according to the human visual system, and it evaluates the image quality through the
image Thumbnailing via Multi-view Face Detection AND Saliency Analysis
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Image thumbnailing is an essential technique to efficiently visualize large-scale consumer photos or image search results. In this paper, we propose a hierarchical multi-view face detection algorithm for image thumbnailing, and a unified framework which aggregates both
An Improved Content Based Image Retrieval Using A Multi-Scale Saliency Model
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AbstractThe data retrieval process needs a storage and search methodology to find the data according to the query inputs. The presented work is focused on the image data retrieval using the query inputs. There are two different kinds of input are frequently used for
SALIENCY BASED ADAPTIVE IMAGE SIGNATURE USING BINARY HOLISTIC IMAGE DESCRIPTOR: A SURVEY
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ABSTRACT Finding all objects in a scene and separating them from the background is known as figure-ground separation. For a figure ground separation problem Introduce a simple image descriptor referred to as the image signature. Then show, within the theoretical
Finding Interesting Parts of an Image: Adding LULU Operators/Discrete Pulse Transform to a Saliency Map
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Abstractthis paper describes an approach to finding visually appealing objects within an image. The technique involves applying the Discrete Pulse Transform (DPT), which is formed with the LULU operator, and applying it to the saliency map. A saliency map is the
FOURIER TRANSFORM BASED SALIENCY DETECTION FOR SKETCH BASED IMAGE RETRIEVAL SYSTEMS
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ABSTRACT Visual Saliency is the perceptual quality that makes an object or pixel region stand out relative to its neighbors and thus capture viewer attention. Thus Saliency models indicate the region of interest. This paper aims at improving the performance of sketch based
Research on saliency prior based image processing algorithm
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AbstractAccording to high development of digital technologies, image processing is more and more import in various fields, such as robot navigator, images classifier. Current image processing model still need large amount of training data to tune processing model and cant
The Kadir Operator Saliency, Scale and Image
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Page 1. The Kadir Operator Saliency, Scale and Image Description Timor Kadir and Michael Brady University of Oxford Page 2. The issuessalientstanding out from the rest,What else is goodAnything bad Page 32. References Kadir, Brady; Saliency, scale and image
SWT based Saliency Detection using Low Level Multi Scale Image Features
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Abstract-Stationary wavelet transform (SWT) achieves translation-invariance by avoiding down sampling, resulting in giving lossless information. In this paper, SWT technique is implemented for creating local and global saliency maps. The performance of the saliency
Survey of Image Retrieval via Visual AttentionSaliency Feature
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AbstractIn the real world applications such as landmark search, copy protection, fake image detection, partial duplicate image retrieval is very important. In the internet era users regularly upload images which are partially duplicate images on the various domains. The
AUTOMATIC IMAGE RETARGETING USING SALIENCY BASED MESH PARAMETERIZATION
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AbstractAutomatic image retargeting is used for large image. That are to be fit in small size display devices. Without any loss of information. our proposed methods one is saliency based mesh parameterization method is used to retarget the image. Stretch-Based Mesh
Re-Ranking Based Image Categorization Using Saliency Driven Nonlinear Diffusion Filtering-A Review
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Abstract: The new technique is proposed for Re-ranking based image categorization using saliency driven nonlinear diffusion filtering. The image categorize based on Re-ranking, using multi-scale information fusion based on the original image. The foreground features,
Self-Organizing Map-Based Color Image Segmentation with Fuzzy C-Means Clustering and Saliency Map
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ABSTRACT Segmentation refers to the process of partitioning a digital image into multiple segments known as super-pixels. Image segmentation is typically used to locate objects and boundaries in images. SOM-K, a new unsupervised natural image segmentation method
Unsupervised Image Cosegmentation Based on Global Clustering and Saliency
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Abstract This thesis introduces a new method for unsupervised image cosegmentation. This problem deals with a collection containing multiple images that are segmented in binary regions, known as object and background of the scene. The objects of interest are visually
LDR Image from HDR by Using Fast and Saliency Based Tone-Mapping Algorithm: A Review
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Abstract-This paper presents a comparatively analysis of the fast and saliency feature based tone mapping technique. After analysis of these techniques we had concluded that fast tonemapping algorithm is most computationally efficient and easy but there may be some
Image Transformation using Modified K-means clustering algorithm for Parallel saliency map
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Abstractto design an image transformation system is Depending on the transform chosen, the input and output images may appear entirely different and have different interpretations. Image Transformation with the help of certain module like input image, image cluster index,
A Novel Approach to Saliency Detection Model and Its Applications in Image Compression
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ABSTRACT Salient region detection in images is very useful for image processing applications like image segmentation, object detection and recognition. In this paper, an improved approach to detect salient region is presented Using saliency detection technique.
CATEGORIZATION OF IMAGE BY RE-RANKING USING SALIENCY DRIVEN NONLINEAR DIFFUSION FILTERING
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Abstract-The new technique is proposed for Re-ranking based image categorization using saliency driven nonlinear diffusion filtering. The image categorize based on Re-ranking, using multi-scale information fusion based on the original image. The foreground features,
Image Resizing By Using Saliency Detection with Selective Dissimilarities Technique Based on User Defined
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AbstractThe human visual system has a remarkable ability to automatically attend to only salient regions, known as focus of attention in complex scenes. This ability enables us to allocate limited perceptual and cognitive resources on task relevant visual input. It is well
Saliency detection and feature matching for image trimming and tracking in active video
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Abstract We develop a new automatic Object of Interest detection method for image trimming and a novel tracking technique in active videos. Both applications consist of salient region detection and feature matching. We deploy a color-saliency weighted Probability-of-
A Survey On Flower Image Retrieval Based On Saliency Map And Feature Extraction
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AbstractContent based Image Retrieval is a growing topic under image processing. The main purpose of CBIR System is to help users to retrieve revelent images based on their contents using several feature extraction technique such as color, texture and shape using
deep image saliency computing IEEE PAPER
Genetic algorithm: A tutorial review
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25 Genetic Algorithm: A Tutorial Review Deep Malya Mukhopadhyay 1 Maricel O. Balitanas 2 Alisherov Farkhod A. 2The original facial images are also resized to the resolution of 32x32 for display purposes.Training Image Feature Map1 Feature Map2 Feature Map3
Learning what matters: combining probabilistic models of 2d and 3d saliency cues
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true probabilities rather than arbitrarily scaled saliency measures allows for deeper, semantically meaningfulgraph cuts for optimal boundaryregion segmentation of objects in nd images.sample consensus: A paradigm for model fitting with applications to image analysis and
Learning Hierarchical Image Representation with Sparsity, Saliency and Locality.
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Deep LearningIn Page 9. YANG, YANG: LEARNING HIERARCHICAL IMAGE REPRESENTATION 9 our experiments, we resize the images so that have the largest dimension is 300 pixels and zero-padding them to have canonical 300 × 300 pixels.
Unsupervised deep feature extraction of hyperspectral images
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Interestingly, it is also observed that, the deeper structures we use, the higher spatial decorrelation of the bestWe introduced the use of the EPLS algorithm to train deep convolu- tional networks in aof the different layers 1st to 7th (in columns) for a subregion of the whole image.
Learning high-level concepts by training a deep network on eye fixations
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on natural images, meaningful high-level features can be learned out using a deep networkhas considered the influence of visual attention on the feature learning in deeper levelsand high-level features from eye fixations, we collect salient regions from each image according to
Attention modeling for face recognition via deep learning
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ap Attention Map Input Image Figure 2: Construct attention model by first RBM in bilinear deep belief network.Dataset The CMU PIE face dataset collected between October and December 2000 contains 68 subjects with a total of 41,368 face images (Sim, et al., 2002).
Salient region detection using contrast-based saliency and watershed segmentation
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WH Ngau, LM Ang, KP Sengon ComputingInformatics 2009 ( , 2009 repo.uum.edu.my to locate these objects using a machine as a human does will require deep understanding of theThe time taken in computing the saliency map is reduced using integral images.map is then used to calculate the average saliency per region on the watershed transformed image.
Learning to detect salient objects with image-level supervision
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Driven by the remarkable success of deep neural net- works (DNNs) in many computer vision areas [23, 14, 11, 47, 48], there has been a recent surge of interests in training DNNsImage-level tags indicate the presence or absence of object categories in the images and are
Detection and classification of breast cancer in whole slide histopathology images using deep convolutional networks
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by training a CNN. The network employed for this task is deeper and thevisualization methods of deep networks for better understanding of the learning process.In medical image analysis, saliency detection on biopsy images is relatively unexplored problem.
Dynamic capacity networks
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2014) have shown that middle layer hints can improve learning in deep and thin2The only pre-processing we perform on the data is converting images to grayscalegiven an input image x. The output sequence S is defined using a collection of N random variables, S1,,SN rep types of in- formation:(i) the dynamics of contours (DC)[9] at each scale, and (ii) the deep image structure, whichExperimental results The proposed strategy for content-based image retrieval has been evaluated with a general-purpose image database of 600 images from the
Deep Gaze I: Boosting Saliency Prediction
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Very deep convolutional networks for large-scale image recognition.Going deeper with convolutions.The central fixation bias in scene viewing: Selecting an optimal viewing po- sition independently of motor biases and image feature distributions.
Deep Level Sets for Salient Object Detection
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Another useful assumption called center bias prior assumes that salient objects tend to be located at the center of images [54, 64These methods tend to fail at complex situations because they dont aware the image content or cant effectively learn theDeep Saliency Networks
Saliency Transfer: An Example-Based Method for Salient Object Detection.
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Image saliency: From intrinsic to extrinsic context. In CVPR, pages 417424. IEEE, 2011.Deep networks for saliency de- tection via local estimation and global search. In CVPR, pages 3183 3192, 2015.Saliency de- tection with a deeper investigation of light field.
Exploiting Visual Salience for the Generation of Referring Expressions.
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iterate through the list of preferred attributes <type, colour, tall, short, wide, narrow, deep, shallow>. This involved generating images of visual scenes from the LIVE system and recording the visual saliencyAfter this, for each image a caption (of the formthe [adj] N ) intended to
Space-variant descriptor sampling for action recognition based on saliency and eye movements
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the same action recognition task as the computer vision algorithms, it is reasonable to assume that they looked at those image regions thatDeep learning techniques, such as convolution and stack- ing, were employed to scale the algorithm to large images and learn
Learning saliency. An ICA based model using Bernoulli mixtures
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Tatler and Baddeley in [1] go through a deep discussion on determining what are the characteristicsin a set of feature bases which cap- ture the linear correlations between the images. from the scene whose value reflects the local degree of interestingness of the image wrt the
Fast saliency based pooling of fisher encoded dense trajectories
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Fisher encoding methodhas proven to be very powerful when applied on images and has last layer on the network pre-trained on ImageNet, on the central crop of the image. A deep convolutional activation
Dense vs sparse: A comparative study of sampling analysis in scene classification of high-resolution remote sensing imagery
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the image, eg by using bag-of- words model or using recently proposed deep learning method the statistics of a collection of natural images instead of the particular image being processed the probability density function of F estimated from a collection of natural images, then the
Attentional Push: A Deep Convolutional Network for Augmenting Image Salience with Shared Attention Modeling in Social Scenes
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quire new and deeper insights into the concept of saliency- based attention tracking [7]. One of the shortcomings of the standardWe presented a deep convolutional convnet which learns to follow the gaze location of the scene ac- tors and augments(i) Input image, (ii) ground
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