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In this article, we present an algorithm to track objects in complex environments like, large variations in scale and orientation, background clutters, illumination changes, pose variation and occlusion. A multilayer perceptron based discriminative appearance model is constructed to distinguish the objects from their cluttered backgrounds. Moments of the binary image are used to estimate scale and...
This paper presents a proposed technique for dual-axis solar tracking system using fusion based approach of an astronomical based estimation and a visual sensor based feedback to locate and track sun position continuously time by time. The astronomical based calculation is used to estimate azimuth and elevation angles of a dual-axis solar power plant with respect to the time and location of the plant...
An objective blur measure is crucial for a variety of image processing applications. Traditional researches concentrate on a model estimating the amount of spatial high frequency. However, human vision detects blurriness might be influenced by the texture of image contents. To address the important issue, this paper presents a new objective metric designed as both measuring the inherent smooth texture...
Object tracking is one of the important tasks for mobile robot, and developing a robust and real-time visual tracking algorithm which can adaptively capture the varying appearance of target under challenging conditions for mobile robot is still an open problem. The main challenges of visual tracking for mobile robot come from variation of target's appearance and disturbance of environment. To cope...
In recent years, violence has considerably increased in the world. In a certain state of Brazil, for example, the homicide rate grew from 16 homicides per 100,000 inhabitants in 2000, to 48 homicides per 100,000 inhabitants in 2014. Police departments worldwide use various types of crime maps, which are generated with diverse techniques, in order to analyze and fight crime. Those types of maps enable...
This paper presents a method that estimates human emotion evoked by visual stimuli using functional magnetic resonance imaging (fMRI) data. First, in our method, preprocessing and masking procedures are applied to the fMRI data. These procedures provide the multiple brain data corresponding to Brodmann areas (BA). In most cases, the dimensionality of fMRI data and the BA data is larger than the number...
In this paper, we propose a tourism category classification method based on estimation of reliable decision. The proposed method performs tourism category classification using location, visual, and textual tag features obtained from tourism images in image sharing services. As the biggest contribution of this paper, the proposed method performs successful classification based on two classification...
In this paper, we propose a method of AUV localization and mapping using visual measurement of underwater structures. Since the inertial navigation system (INS) of AUV suffers from drift, visual observation of fixed objects can enhance the localization performance. In a framework of pose graph optimization, depth map estimation of underwater structures and tracing of AUV trajectory are concurrently...
In most artificial vision systems the quality of acquired images is directly related with the amount of information that can be obtained from them, and, particularly in underwater robotics applications involving monitoring and inspection tasks this is crucial. Statistical learning methods like Markov Random Fields with Belief Propagation (MRF-BP) provide a solution by using existing essential correlations...
Artificial fish-swarm algorithm is a novel method to search global optimum, which is typical application of behaviorism in artificial intelligence. Compared with traditional method it is more portability and stability. This paper, based on the loss function to increase the enterprise benefit, brings forward an optimized criterion of setting threshold to relieve the security officer work in the chemical...
The topic presented in this paper covers statistical studies on illumination conducted using specialised software dedicated to such simulations. A pre-designed computer visualisation of illumination, which included zonal illuminations of a selected architectural structure was modified by a selected group of respondents. As a result of responders individual aesthetic preferences sets of average luminance...
Computational visual atention models aims to emulate the Human Visual System performance in selecting relevant features for efficient visual scene processing. As a result, visual saliency maps highlights relevant visual patterns in an image, possibly associated with objects or specific concepts. In the analysis of medical images, this allows the radiologist or clinical expert to focus the attention...
BGM (background music) of a video plays an important role for making a video impressive. Although a large number of royalty-free music clips are available on the web, it is still difficult for amateur video creators to select appropriate music clips for their videos. In this paper, we propose a computational method for estimating the impression of a video from auditory and visual features of a video...
Hair is one of the most recognizable parts of a human body, which is essential for the digitization of compelling virtual avatars but also one of the most challenging to create. In this paper, we present a single-view hair modeling technique for generating visually plausible strand-based 3D hair models. This is made possible by an effective high-precision 2D strand tracing algorithm, which explicitly...
Density estimation based visual object counting (DE-VOC) methods estimate the counts of an image by integrating over its predicted density map. They perform effectively but inefficiently. This paper proposes a fast DE-VOC method but maintains its effectiveness. Essentially, the feature space of image patches from VOC can be clustered into subspaces, and the examples of each subspace can be collected...
This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art...
Structure tensor analysis on epipolar plane images (EPIs) is a successful approach to estimate disparity from a light field, i.e. a dense set of multi-view images. However, the disparity range allowable for the light field is limited, because the estimation becomes less accurate as the range of disparities become larger. To overcome this limitation, we propose a new method called sheared EPI analysis,...
This paper presents a new image retargeting method that explores blur information. Given the input image, we compute the blur map and estimate in-focus regions. For retargeting, we first try to crop image boundaries as much as possible (preserving in-focus regions). If cropping is not enough, we use seam carving exploring a novel blur-aware energy function that concentrates the seams in blurred regions...
Robust scale and rotation estimation is an important and challenging problem in visual object tracking. There have been proposed many sophisticated trackers to track the location of a target accurately, but most of them do not take much attention to the scale and rotation estimation. Inspired by the success of the correlation filters in visual tracking, we proposed a novel scale-and-rotation correlation...
This paper proposes a method that blindly predicts preference order between inpainted images, aiming at selecting the best one from a plurality of results. Image inpainting, which removes unwanted regions and restores them, has attracted recent attention. However, it is known that the inpainting result varies largely with the method used for inpainting and the parameters set. Thus, in a typical use...
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