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Unmanned aircraft flying beyond line of sight in uncontrolled airspace need to maintain adequate separation from local inclement weather patterns for regulatory compliance and operational safety. Although commercial solutions for ‘weather avoidance’ exist, they are tailored to manned aviation and as such either lack the accuracy or the size, weight, and power (SWaP) requirements of small Unmanned...
To deal with the problem of lack of subjective visual perception in texture features exacting of digital camouflage, a new extraction arithmetic based on human visual perception and isoperimetric theory is proposed in this paper. The method firstly constructs edge weight function according to human visual perception, then selects isoperimetric ratio as a as a criterion to determine the optimal threshold...
Loop closure detection (LCD) is a process trying to find a match between the current and a previously visited locations in SLAM. The bag of words (BoW) is a popular approach used in LCD, however, limited by perceptual aliasing primarily due to vector quantization. This paper proposes an improved method of the BoW called spatial partitioning BoW(SPBoW). We first apply scene segmentation to integrate...
A new algorithm for automatic segmentation of moving objects in video based on spatio-temporal saliency and Neutro-Connectedness is presented in this paper. First, we propose a simple model to compute video saliency by combining initial saliency maps computed in spatial and temporal domains. Then, based on the detected spatiotemporal saliency map and temporal superpixels, initial background and foreground...
Vision localization apple bagging robot is researched in this paper for young apples. The key technologies of the young fruit stereoscopic images recognizing and positioning are studied in the visible light of the natural environment. Firstly, the Otsu segmentation algorithm is used to preprocess the collected young apple images. Secondly, the improved connected component labeling algorithm is used...
Visual place recognition under difficult perceptual conditions remains a challenging problem due to changing weather conditions, illumination and seasons. Long-term visual navigation approaches for robot localization should be robust to these dynamics of the environment. Existing methods typically leverage feature descriptions of whole images or image regions from Deep Convolutional Neural Networks...
Image processing is an inevitable tool for visual tracking. Visual object tracking is a very hot area of research in the computer vision. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and in general, deal with the extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the...
We present a framework for fast target detection in real-world robotics applications. Considering that an intelligent agent attends to a task-specific object target during execution, our goal is to detect the object efficiently. We propose the concept of early recognition, which influences the candidate proposal process to achieve fast and reliable detection performance. To check the target constraints...
Recognition of human manipulation actions together with the analysis and execution by a robot is an important issue. Also, perception of spatial relationships between objects is central to understanding the meaning of manipulation actions. Here we would like to merge these two notions and analyze manipulation actions using symbolic spatial relations between objects in the scene. Specifically, we define...
Visual scene decomposition into semantic entities is one of the major challenges when creating a reliable object grasping system. Recently, we introduced a bottom-up hierarchical clustering approach [1] which is able to segment objects and parts in a scene. In this paper, we introduce a transform from such a segmentation into a corresponding, hierarchical saliency function. In comprehensive experiments...
As an attractive area of application in the sphere of cultural heritage, in recent years automatic analysis of ancient coins has been attracting an increasing amount of research attention from the computer vision community. Recent work has demonstrated that the existing state of the art performs extremely poorly when applied on images acquired in realistic conditions. One of the reasons behind this...
Horizon or skyline detection plays a vital role towards mountainous visual geo-localization, however most of the recently proposed visual geo-localization approaches rely on user-in-the-loop skyline detection methods. Detecting such a segmenting boundary fully autonomously would definitely be a step forward for these localization approaches. This paper provides a quantitative comparison of four such...
Segmentation of biomedical images is a challenging task, especially when there is low quality or missing data. The use of prior information can provide significant assistance for obtaining more accurate results. In this paper we propose a new approach for dendritic spine segmentation from microscopic images over time, which is motivated by incorporating shape information from previous time points...
Microscopic analysis of histological sections is considered the “gold standard” to verify structural parcellations in the human brain. Its high resolution allows the study of laminar and columnar patterns of cell distributions, which build an important basis for the simulation of cortical areas and networks. However, such cytoarchitectonic mapping is a semiautomatic, time consuming process that does...
Given a large-scale video archive of surgical interventions and a medical image showing a specific moment of an operation, how to find the most image-related videos efficiently without the utilization of additional semantic characteristics? In this paper, we investigate a novel content-based approach of linking medical images with relevant video segments arising from endoscopic procedures. We propose...
It is important to generate both interesting and representative video summary for massive videos. This work proposes a new method to generate dynamic video summary using multiple features and image quality without human's involvement in the whole procedure. Specifically, we first split a video into several video clips. Second, a set of features including visual attention, exposure of light, saturation,...
This paper present a query-by-example word spotting in handwritten Arabic documents, based on Harris detector and Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representations. First, the interest points are automatically extracted from the images using Harris detector, then, we use SIFT descriptor...
The ability to localize visual objects that are associated with an audio source and at the same time seperate the audio signal is a corner stone in several audio-visual signal processing applications. Past efforts usually focused on localizing only the visual objects, without audio separation abilities. Besides, they often rely computational expensive pre-processing steps to segment images pixels...
In this work, we present an automated inspection approach to assist remote visual examinations of nuclear power plant components. An automated approach would require detecting often low contrast cracks that could be surrounded by or even within textures with similar appearances such as welding, scratches, and grind marks. We propose a crack segmentation method for remote visual examination videos...
We propose to leverage concept-level representations for complex event recognition in photographs given limited training examples. We introduce a novel framework to discover event concept attributes from the web and use that to extract semantic features from images and classify them into social event categories with few training examples. Discovered concepts include a variety of objects, scenes, actions...
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