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In this paper, we propose an instrumentation and computer vision pipeline that allows automatic object detection on images taken from multiple experimental set ups. We demonstrate the approach by autonomously counting intoxicated flies in the FLORIDA assay. The assay measures the effect of ethanol exposure onto the ability of a vinegar fly Drosophila melanogaster to right itself. The analysis consists...
Image segmentation is used in computer vision, medical imaging, and biological imaging to locate object boundaries and to group similar pixels together to form a set of coherent image regions. The important factors of clustering are similarity, proximity, and good continuation, which lead to visually meaningful segmentation. On the contrary, there are some problems of visual grouping such as over-segmentation,...
Texture in images is used as a cue for various computer vision tasks like segmentation, classification and object detection. In this paper, we explore a variation of texture detection technique using oriented Gaussian derivative filters with multiple scales and orientations. After obtaining the filter responses at each pixel location, K-means clustering is used to determine regions with different...
The segmentation of video sequences into regions underlying a coherent motion is one of the most useful processing for video analysis and coding. In this paper, we propose an algorithm that exploits the advantages of both top-down and bottom-up techniques for motion field segmentation. To remove camera motion, a global motion estimation and compensation is first performed. Local motion estimation...
The segmentation of video sequences into regions underlying a coherent motion is one of the most useful processing for video analysis and coding. In this paper, we propose an algorithm that exploits the advantages of both top-down and bottom-up techniques for motion field segmentation. To remove camera motion, a global motion estimation and compensation is first performed. Local motion estimation...
Multiphase level set model is sensitive to initial contour curve and has huge computation in the process of the multiple objects' segmentation. This paper presents a novel Image segmentation method for multiphase scenario, which initialize the multiphase level set function by coarse image segmentation using fuzzy C-means clustering algorithm and apply graph cut algorithm to acquire multiphase output...
A superpixel is an image patch which is better aligned with intensity edges than a rectangular patch. Superpixels are perceptually consistent units which carry more information than pixels and adhere well to image boundaries. Nowadays superpixels are widely used for segmentation in computer vision and biomedicai applications. There are many approaches to generate superpixels such as SLIC, QuickShift,...
Segmentation and clustering are common pre-processing tasks in many image understanding and computer vision applications. In some of these applications, expert users can often provide knowledge about which pixels or regions in an image should be grouped together, guiding the clustering or segmentation process to yield more meaningful results than could be achieved by fully automatic algorithms. In...
In this work, we deal with the problem of moving object detection using a non-parametric tool represented by the Gaussian process for classification. The technique used relies on the background subtraction approach for motion detection. In this context, a segmentation step is first implemented for pixel clustering before a binary Gaussian process classifier is applied to determine which pixel cluster...
The unsupervised color image segmentation competition is taking place in conjunction with the ICPR 2014 conference. It aims to promote evaluation of unsupervised color image segmentation algorithms using publicly available data sets. The results evaluation is based on the standard performance assessment methodology using the online web verification server. We present in this paper the top six preliminary...
Image segmentation is a fundamental process in computer vision applications. This paper presents a novel method to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized...
In this paper, indoor environment classification and interpretation algorithm is proposed. Proposed algorithm needs low computation power and low payload thus enabling micro air vehicle (MAV) to quickly react and navigate. Here indoor environment is classified into corridor, staircase, and open space by using image edge gist descriptors and a neural network classifier. Use of some predetermined thresholds...
In this paper, we propose an interactive clothing image segmentation method based on super pixels and Graph Cuts. Firstly, we process the image from pixels to super pixels with the method of SLIC to reduce the computational loads and lower the effect of noise, and then a graph is constructed using super pixels as nodes. Finally, min-cut/max-flow algorithm is applied to solve the energy function. In...
In this paper, we study an approach for discovering brand associations by leveraging large-scale online photo collections contributed by the general public. Brand Associations, one of central concepts in marketing, describe customers' top-of-mind attitudes or feelings toward a brand. (e.g. what comes to mind when you think of Burberry?) Traditionally, brand associations are measured by analyzing the...
In order to address the problem that the pedestrian segmentation in infrared image is easy to be interfered by the human pose and noise, this paper presents a pedestrian segmentation algorithm in infrared images employing super pixel and conditional random filed. Owing to accelerate the computation, the algorithm employs the simple linear iterative clustering algorithm to divide the image into some...
In this paper we introduce the Reduction Sweep algorithm, a novel graph-based image segmentation algorithm that is designed for easy parallelization. It is based on a clustering approach focusing on local image characteristics. Each pixel is compared with its neighbors in an implicitly independent manner, and those deemed sufficiently similar according to a color criterion are joined. We achieve fast...
A method for automatic creation of a semantic texture database is introduced, which exploits the cumulative knowledge that exists in the image tags on the World Wide Web. In the first step of the method, a number of images are retrieved from the Web using the text search option provided by search engines by querying simple notions (e.g. sky, grass water, etc.). These images are segmented into a number...
One of the most important challenging issues in visual surveillance systems is about detecting moving objects from video sequences captured by an active camera. In contrast to the other proposed methods which are focused on fixed cameras, approaches based on moving cameras are more complex, because making a distinction between moving object and background is difficult. Thus, detecting moving objects...
In this paper, we proposed a super pixel based depth map propagation algorithm for the application in 2D to 3D video conversion. The proposed algorithm employs four main processes to generate depth maps for all frames in video sequences. First, the depth map of the key frames in the input sequences are generated by manual work. Second, the frames in the input sequences are over-segmented by Simple...
Image segmentation is one of the most important research areas in image processing and computer vision, and is a key step in image processing and image analysis. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. Based on the measure of medium truth degree, this paper presents a novel image segmentation method by introducing the distance...
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