The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We propose a stereo vision based obstacle detection and scene segmentation algorithm appropriate for autonomous vehicles. Our algorithm is based on an innovative extension of the Stixel world, which neglects computing a disparity map. Ground plane and stixel distance estimation is improved by exploiting an online learned color model. Furthermore, the stixel height estimation is leveraged by an innovative...
We tackle the challenging problem of hand gesture tracking with 2D webcams, which is a promising enabler for human computer interaction. Recent studies have proposed many methods for object tracking. However, unlike the other ob-jects, the particularities of hand make it difficult to be represented by common-used feature descriptors. In this paper, we analyze the key points in hand tracking and take...
This study proposes the development of a simple remote-controlled daily assistive robot to assist physically challenged individuals. Specifically, we present a method for target object selection using a single click on a graphical user interface. Using this information, the robot can automatically estimate the unknown target object region to plan to grasp and fetch the object. The challenging task...
In apple harvesting robot, the first key part is the machine vision system. Identifying single objects from fruit images is the first and foremost task in machine vision system. However, the main problem affecting the identification of single fruits is that fruit regions in image taken in unstructured orchard environment are overlapping in some cases. On the basis of studies on fruit image segmentation...
With the development of digital multimedia technologies, image matting has gained increasing interests from both academic and industrial communities. The purpose of image matting is to precisely extract the foreground objects with arbitrary shapes from an image or a video frame for further editing. It is generally known that image matting is inherently an ill-posed problem because we need to output...
Chroma-keying is an important technique for image/video background replacement, which is heavily used in film production, video game industry and news casting. In chroma-keying system, the foreground objects are shot in front of solid color background. In conventional chroma-keying systems, difference and clustering based algorithms are mainly used to separate foreground from background. However,...
In this paper, a novel matting method is proposed to automatically detect and separate foreground, background and transitional (unknown) regions in a color image. In order to detect the background color, K-means clustering in YCbCr color space is firstly used to classify the background colors into a limited number of clusters. Then the spatial information is further used to refine the background and...
The measurement or evaluation and clinical significance of human sperm morphology has always been and still is a controversial aspect of the semen analysis for the determination of a male's fertility potential. The evaluation of sperm size, shape and morphological smear characteristics should be assesed by carefully observing a stained sperm sample under a microscope. In order to avoid subjectivity,...
This paper proposes a method to merge the real and virtual world in snapshots captured by a mobile camera. While snapshots are usually captured in a dynamic scene that temporally changes the appearance, we developed a pose estimation method for a mobile camera by using depth sensors installed in the capturing environment. In order to generate a fine MR (Mixed-Reality) image, our method segments overlapping...
Clustering is a popular tool for exploratory data analysis, such as K-means and Fuzzy C-mean. A simple estimation the number of classes for segmented areas (K) in satellite imagery application is often needed in advance as an input parameter to the K-means algorithm. In this paper, a method has been developed to estimate the number of classes for segmented areas in satellite imagery clustering application...
In this paper, we propose an supervised color image segmentation scheme using homotopy continuation method and Compound Markov Random Field (CMRF) model with Bilevel Binary Line Fields. The scheme is specifically meant to preserve weak edges besides the well defined strong edges. Ohta (I1, I2, I3) model is used as the color model for image segmentation and we propose a compound MRF model taking care...
This paper proposes a system to relate objects in an image using occlusion cues and arrange them according to depth. The system does not rely on any a priori knowledge of the scene structure and focuses on detecting specific points, such as T-junctions, to infer the depth relationships between objects in the scene. The system makes extensive use of the Binary Partition Tree (BPT) as the segmentation...
In this paper we use humans and chimpanzees brain MRI databases to develop methods for evaluating global brain asymmetries. We perform brain segmentation and hemispheric surface extraction on both populations. The human brain segmentation pipeline is adapted to chimpanzees in order to obtain results of good quality. To alleviate the problems due to cortical variability we propose a mesh processing...
Color Filter Array (CFA) interpolation is an integral part of image processing pipeline for single sensor digital cameras. Many CFA algorithms have been proposed over the years to improve resulting image quality. One such algorithm is the highly successful Directional Linear Minimum Mean-Square Error Estimation (DLMMSE) method. We make several observations on this algorithm and propose a new method...
Object detection and recognition algorithms are an integral part of the architecture of many modern image processing systems employing Computer Vision (CV) techniques. In this paper we describe our work in the area of segmentation and recognition of simple objects in mobile phone imagery. Given an image of several objects on a structured background, we show how these objects can be segmented efficiently...
We propose a method for estimating demosaicing algorithms from image noise variance. We show that the noise variance in interpolated pixels becomes smaller than that of directly observed pixels without interpolation. Our method capitalizes on the spatial variation of image noise variance in demosaiced images to estimate the color filter array patterns and demosaicing algorithms. We verify the effectiveness...
We present a novel and efficient multi-view depth map enhancement method proposed as a post-processing of initially estimated depth maps. The proposed method is based on edge, motion and scene depth-range adaptive median filtering and allows for an improved quality of virtual view synthesis. To enforce the spatial, temporal and inter-view coherence in the multi-view depth maps, the median filtering...
Parametric density estimation is widely used to solve many image processing problems. We examined the parametric estimation using linear combination of 1D Gaussians in many works. In this work, we extend our model to estimate density of the colors in color images. We approximate the marginal density of each class in the empirical probability density function by a 3D Gaussian distribution. Then, the...
As an extremely powerful probability model, Gaussian mixture model (GMM) has been widely used in the fields of pattern recognition, information processing and data mining. However, in many practical applications, the number of the components is unknown. In the case, model selection of GMM, i.e., the selection of the number of the components in the mixture, has been a rather difficult problem. Recently,...
This paper presents a dynamic background modeling approach for foreground segmentation. The classification between foreground and background is based on Bayes decision rule. The posterior probability of a pixel being observed as a background or a foreground is directly estimated based on the occurrence frequency of its quantized version. Experimental results show that the presented method can be performed...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.