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We present an improved version of the Simple Linear Iterative Clustering (SLIC) superpixel segmentation. Unlike SLIC, our algorithm is non-iterative, enforces connectivity from the start, requires lesser memory, and is faster. Relying on the superpixel boundaries obtained using our algorithm, we also present a polygonal partitioning algorithm. We demonstrate that our superpixels as well as the polygonal...
In this paper, we propose a multiple line extraction method from multimodal data points in high dimensional space. It can sparsely represent multimodal sensor network data by utilizing high correlation among channels in the data. We exploit the idea of Color Lines, which is a model using high correlation among RGB channels in computer vision. It represents real color images as a collection of multiple...
In this paper, we present a novel approach to estimate the relative depth of regions in monocular images. There are several contributions. First, the task of monocular depth estimation is considered as a learning-to-rank problem which offers several advantages compared to regression approaches. Second, monocular depth clues of human perception are modeled in a systematic manner. Third, we show that...
This paper presents a computational framework for accurately estimating the disparity map of plenoptic images. The proposed framework is based on the variational principle and provides intrinsic sub-pixel precision. The light-field motion tensor introduced in the framework allows us to combine advanced robust data terms as well as provides explicit treatments for different color channels. A warping...
The quantity and diversity of data in Light-Field videos makes this content valuable for many applications such as mixed and augmented reality or post-production in the movie industry. Some of such applications require a large parallax between the different views of the Light-Field, making the multi-view capture a better option than plenoptic cameras. In this paper we propose a dataset and a complete...
The last years have seen a quick rise of digital photography. Plenoptic cameras provide extended capabilities with respect to previous models. Multi-focus cameras enlarge the depth-of-field of the pictures using different focal lengths in the lens composing the array, but questions still arise on how to select and use these lenses. In this work a further insight on the lens selection was made, and...
This paper proposes a method that separates the region of each leaf from an image of occluded leaves and produces a set of single-leaf images as an output. To identify the region of a single leaf, intersection points and direction field are required. An intersection point, which is defined as a concave point between leaves, is used as the starting position of leaf estimation process. Direction field,...
This paper proposed real-time lane detection system for automotive application based on field programmable gate array (FPGA). The proposed system has two main. The first one is pre-processing with statistic and blob detection, and the second one is real-time lane detection algorithm. To meet real-time system, using the simple algorithm on a clear image by pre-processing. Experiments and comparisons...
This paper proposes a method for estimating the surface of transparent objects based on light field convergency. The light field convergency represents the degree of convergence of the light field at each point. The proposed method utilizes local photo consistency, which is one of characteristics of the light field convergency. Around a boundary contour, a point that is visible from viewpoints with...
Image road detection in unstructured environments is a crucial and challenging problem in the application of mobile robots and autonomous vehicles. In this paper, we present an effective and computationally efficient solution to segment the road region for structured and unstructured roads. We propose a new method that incorporates two different approaches: road detection based on the vanishing point...
In this paper, the small mobile robot for use in block type IoT(Internet of things) education robot aimed for children and infants is designed. As the robot moves on real world structure built by blocks, the virtual robot on the augmented reality displayed on the screen moves at the same time. Since the real world and virtual world should match precisely, accurate position and velocity estimation...
We present a new way to combine the propagated flow in image pyramid and dense correspondences from descriptor matching for large displacement optical flow estimation. Because the matches and the flow propagated from the coarser level in image pyramid are possibly wrong, our method uses color-based weighted linear interpolation to reduce the wrong initial flow and alleviate over-smoothing, instead...
Due to the advent of the aging society, homecare is more and more important. In this paper, we design and implement the contactless pulse rate measurement method based on the Android smart TV, which allows the user to measure their pulse rate without requiring of contact sensors. This framework provides a convenient measurement environment for homecare. The results of the experiment show the presenting...
The method of image defogging mainly includes two aspects: image enhancement and image restoration. This article mainly focus on the image restoration. First of all, it studies the He's defogging algorithm based on dark channel prior and make some improvement based on this theory. Aiming at solving the defects of inaccurate estimation of atmospheric light and long time running of He's algorithm, the...
This paper proposes a novel method combining dark channel prior (DCP) and bright channel prior (BCP) for single image dehazing. The proposed method achieves airlight approximations by implementing numerical proximity of atmospheric light, which use the average value of the DCP and BCP. Meanwhile, in order to reduce computational time, a fast guided filtration method is used for the transmission map...
Saliency detection becomes a crucial requirement for numerous computer vison application. Conventional manifold ranking models have been widely used for saliency detection because it can measure similarity efficiently between the regions, but most of them make use of color and texture information and location information of objects didn't be well exploited, so it cannot work properly when objects...
In this paper we study single image haze removal techniques on outdoor images for visibility enhancement in foggy weather conditions. Haze removal techniques based on dark channel prior model have used different filters for estimating the transmission. We have studied effect of using different filters along with the fundamental mean and gaussian filters in the visibility enhancement in foggy conditions...
Underwater images suffer from low contrast and color distortion due to the existence of dust-like particles and light attenuation. Some previous works using the patch-based priors, e.g. adaptations of the dark channel prior, cannot achieve satisfactory results in both contrast enhancement and color restoration in the underwater environment. In this paper, we propose a novel underwater image restoration...
To overcome the degraded images taken in hazy weather, an adaptive restoration method based on improved contrast enhanced restoration was proposed. Firstly, by quadtree subdivision searching method, the sky area of multi-channel polarization image are extracted automatically, and the atmospheric light and degree of polarization are calculated; Second, scene depth information of image are calculated...
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...
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