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In this paper, we propose an accurate edge detector using richer convolutional features (RCF). Since objects in natural images possess various scales and aspect ratios, learning the rich hierarchical representations is very critical for edge detection. CNNs have been proved to be effective for this task. In addition, the convolutional features in CNNs gradually become coarser with the increase of...
Separating an image into reflectance and shading layers poses a challenge for learning approaches because no large corpus of precise and realistic ground truth decompositions exists. The Intrinsic Images in the Wild (IIW) dataset provides a sparse set of relative human reflectance judgments, which serves as a standard benchmark for intrinsic images. A number of methods use IIW to learn statistical...
Collecting fully annotated image datasets is challenging and expensive. Many types of weak supervision have been explored: weak manual annotations, web search results, temporal continuity, ambient sound and others. We focus on one particular unexplored mode: visual questions that are asked about images. The key observation that inspires our work is that the question itself provides useful information...
One of the most frequently applied low-level operations in computer vision is the conversion of an RGB camera image into its luminance representation. This is also one of the most incorrectly applied operations. Even our most trusted softwares, Matlab and OpenCV, do not perform luminance conversion correctly. In this paper, we examine the main factors that make proper RGB to luminance conversion difficult,...
Shadow removal is a challenging task as it requires the detection/annotation of shadows as well as semantic understanding of the scene. In this paper, we propose an automatic and end-to-end deep neural network (DeshadowNet) to tackle these problems in a unified manner. DeshadowNet is designed with a multi-context architecture, where the output shadow matte is predicted by embedding information from...
Disaster robotics poses particular challenges for computer vision, both in terms of image characteristics (due to motion blur, difficult light conditions, lack of up/down orientation, etc.), and in terms of learning data (limited availability, difficulty of annotation due to image quality, etc.). We developed a system for real-time scene-parsing, intended for use in a support system for operators...
Single feature of pedestrian is difficult to accurately describe the target using traditional algorithms. A new reidentification algorithm combing global features and local features with different distance metric function is introduced. First, weighted color histogram feature for whole pedestrian is extracted and combined with Bhattacharyya distance to roughly recognize targets. Then pedestrians’...
this work considers the algorithm of mobile robot recognition and localization on the basis of color patterns, applied in robosoccer. For exact position definition of mobile robots and a ball in robosoccer it is necessary to analyze the image received from camera. Whereas each of these objects on the image has the color pattern consisting of circles, the first step of algorithm is detecting of circles...
Underwater images are known to be strongly deteriorated by a combination of wavelength-dependent light attenuation and scattering. This results in complex color casts that depend both on the scene depth map and on the light spectrum. Color transfer, which is a technique of choice to counterbalance color casts, assumes stationary casts, defined by global parameters, and is therefore not directly applicable...
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,...
In the present investigation the images with the minimum pixelation required for the inspections of maintenance inside the electrical substation are indicated. In addition, three polynomial functions are obtained based on the heat radiation of the half-voltage disconnecting switches, since these contain the highest temperature values in the images captured in a range between −3 and 39 degrees Celsius...
In this paper, we present a complete change detection system named multimode background subtraction. The universal nature of system allows it to robustly handle multitude of challenges associated with video change detection, such as illumination changes, dynamic background, camera jitter, and moving camera. The system comprises multiple innovative mechanisms in background modeling, model update, pixel...
In the paper, different variations of solving the problem of the visual odometry for a mobile robot with short-baseline stereo camera are investigated, and a conclusion on the suitability of the approaches considered is done.
Action recognition has been an active research area in computer vision community during the recent years. However, it is still a challenging task due to the difficulties mainly resulted from the background clutter, illumination changes, large intra-class variation and noise. In this paper, we aim to develop an action recognition approach by navigating focus of attention (action region) with saliency...
In this paper, we proposed a seam carving based refinement method to refine and produce superpixels. The proposed method can refine existing superpixels by repeating the splitting process. There are two major steps. The first is choosing a superpixel candidate by analyzing color variances; the second is splitting a superpixel into 4 by dynamic programming. The experimental results show that the proposed...
Image matting is one of the most common image processing techniques, because it is often necessary to extract the desired foreground object from the original image and then to composite the extracted foreground with the another background. Over the years, there have been lots of commercial image processing tools or softwares which can support the human beings this function, such as photoshop, photoimpact...
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...
Accessibility problems such as obstacles on sidewalks can make navigation dangerous for the visually impaired. Detecting these accessibility problems using embedded cameras is a plausible remedy. However, current computer vision algorithms for object detection rely on exhaustive search with high-dimensional features that present a heavy computational burden and incur a long latency, making them non-ideal...
Computer science is involved to the greater extent in agricultural and food science these days. Many Artificial Intelligence and soft computing techniques and technologies are used for classification and defect detection of various products and thus helps in Better quality product for the end users. In this paper we focus on the standing of Arecanut in global and Indian market and usage of computer...
Qualitative motion analysis with motion magnification techniques opened a new dimension to videos by revealing imperceptible information hidden in small movements. Those movements can contain information on neurocognitive and affective states and thus could be a novel source of information during driving or neurocognitive experiments, complementing secondary sensors in the respective setup.
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