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Salient Object Detection (SOD) has received much attention from the research community due to its increasing applications in the areas such as object detection and recognition, image editing, image and video compression, video summarization and so on. Most of the SOD methods are proposed in literature presuming that the digital images in which salient objects is to be detected, are free from any kind...
It is often needed to compress images with providing certain properties or quality. Wavelet based coders SPIHT and JPEG2000 easily produce a desired compression ratio but not quality especially if one deals with compressing images corrupted by noise for which specific behavior of quality metrics on compression ratio (CR) or bpp might be observed. In particular, optimal operation point (OOP) where...
In this paper, we present a scene recognition framework, which could process the images and recognize the scene in the images. We demonstrate and evaluate the performance of our system on a dataset of Oxford typical landmarks. In this paper, we put forward a novel method of local k-meriod for building a vocabulary and introduce a novel quantization method of soft-assignment based on the Gaussian mixture...
Recent image steganographic approaches considers perceptual characteristics of the human visual system (HVS), and often use edge detection to express them. In practice, there exist perceptually salient regions for HVS in an image according to visual attention. Moreover, HVS has different sensitivities to luminance contrast and structure of the image, i.e. Pattern masking. To enhance the security of...
The task of large-area visual monitoring for the protection of critical and public infrastructures calls for reliable automated visual surveillance systems. Reliability in this context implies that a high detection accuracy of critical events shall be maintained independent from observation conditions, appearance and pose variations of observed objects (persons, cars), while accomplishing a low-rate...
When exposed to visual perturbations, the motor system rapidly learns to reduce errors through adaptation of future motor commands. However, in cerebellar and stroke patients with proprioceptive impairments, motor adaptation rates are significantly slower. A recent study suggests that adaptation rates may be modulated by the stability of perturbations and the history of errors. We hypothesize that...
In this paper, an extraction for brain-controlled wheelchair by applying nonlinear adaptive filter on EEG-SSVEP is proposed. A four-choice signal paradigm with differents frequencies (i.e., from 6 to 9 Hz for left, right, bottom, and top, respectively) is used to stimulate the four subjects (about 25±1 years old) in the experiment. The experimental results show that the application of the extraction...
In this paper, we propose a new paradigm for human-robot collaboration. In this paradigm, the collaboration properly takes advantage of the superior visual performance of the humans and the field exploration capabilities of robots, allowing the robot to only ask humans for help when needed. More specifically, we consider a robotic field exploration and classification task with limited communications...
This paper introduces a novel secure channel selection rule for spatial image steganography. In this scheme, there are two factors considered to identify a pixel, which causes less distortion to cover image, to be modified in data hiding. The first one is an average difference between considered pixel and its neighbors. The value of the considered pixel is the second employed factor. Obtained experimental...
This paper presents a novel architecture for audio-visual saliency detection using event-based visual sensors and traditional microphones installed on the head of a humanoid robot. In the context of collision detection, salient sensory events must be detected at the same time in vision and in the auditory domain. Real collisions in the visual space can be distinguished from fake ones (e.g. due to...
Functional magnetic resonance imaging (fMRI) has become a common tool in investigating brain activities on human subjects. Although each region of the brain was thought to be independent and responsible only for particular tasks and specialized functions, recent studies have shown that different regions of the brain interact with each other in performing specific tasks or even during the resting state...
In this paper, we examine the relation between onomatopoeia and images using a large number of Web images. The objective of this paper is to examine if the images corresponding to Japanese onomatopoeia words which express the feeling of visual appearance can be recognized by the state-of-the-art visual recognition methods. In our work, first, we collect the images corresponding to onomatopoeia words...
Due to its psychological and physiological interpretation of naturally occurring data, Nonnegative Matrix Factorization (NMF) has attracted considerable attention for learning effective representation for images. And its graph-regularized extensions have shown promising results by exploiting the low dimensional manifold structure of data. Actually, their performance can be further improved because...
Synchrophasors are the state-of-the-art measuring sensors that sense voltage, current, or frequency with high data rate. This paper presents an approach to analyze the streaming smart-grid data generated by synchrophasors. A novel unit-circle representation is used to visualize the real-time phasor data. A Density based clustering (DBSCAN) method is proposed to cluster the phasor data to detect bad-data...
In the present work a new approach for maximum depth of ultrasound signal visualization has been proposed by means of a tissue mimicking phantoms: the novel method is based on a threshold on the tangent applied to the mean depth profile that is drawn by averaging adjacent columns in the diagnostic image. It has been implemented and preliminary tested on three different diagnostic systems equipped...
Estimating the ground plane is often one of the first steps in geometric reasoning processes as it offers easily accessible context knowledge. Especially unconstrained platforms that capture video from egocentric viewpoints can benefit from such knowledge in various ways. A key requirement here is keeping orientation, which can be greatly achieved by keeping track of the ground. We present an approach...
We describe using auralization to monitor process stack and netstat status on a server or small group of servers. Using the auditory channel is especially useful for monitoring because it can be done without taking much attention. Our contribution is to suggest generating noise-like sounds that more naturally fade into the background, and are less fatiguing over long monitoring sessions. Although...
The Environmental Impact Assessment (EIA) is an environmental management instrument implemented worldwide. In the last years the development of Wave Energy Converter (WEC) influenced environmental research to quantify impacts on marine life. In this paper we present a case study of EIA: a real application and study of device installed in Tirren Sea (near Castellammare — Sicily).
Robust, scalable place recognition is a core competency for many robotic applications. However, when revisiting places over and over, many state-of-the-art approaches exhibit reduced performance in terms of computation and memory complexity and in terms of accuracy. For successful deployment of robots over long time scales, we must develop algorithms that get better with repeated visits to the same...
Geographic Information System (GIS) data is a valuable asset that should be protected using digital rights management (DRM) techniques. This paper introduces a new technique for watermarking city maps by altering a basic parameter of a road segment, namely its width to length ratio. A watermark is embedded in the map using an appropriate quantization of this ratio. The watermarked map retains its...
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