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Underwater image reconstruction methods require the knowledge of wideband attenuation coefficients per color channel. Current estimation methods for these coefficients require specialized hardware or multiple images, and none of them leverage the multitude of existing ocean optical measurements as priors. Here, we aim to constrain the set of physically-feasible wideband attenuation coefficients in...
We present a novel method that allows for simultaneous geometric and radiometric calibration of a projector-camera pair. It is simple and does not require specialized hardware. We prewarp and align a specially designed projection pattern onto a printed pattern of different colorimetric properties. After capturing the patterns in several orientations, we perform geometric calibration by estimating...
In this paper, we propose a consistent-aware deep learning (CADL) framework for person re-identification in a camera network. Unlike most existing person re-identification methods which identify whether two body images are from the same person, our approach aims to obtain the maximal correct matches for the whole camera network. Different from recently proposed camera network based re-identification...
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,...
We present a method for radiometric calibration of cameras from a single image that contains a human face. This technique takes advantage of a low-rank property that exists among certain skin albedo gradients because of the pigments within the skin. This property becomes distorted in images that are captured with a non-linear camera response function, and we perform radiometric calibration by solving...
Night beats with alternating current (AC) illumination. By passively sensing this beat, we reveal new scene information which includes: the type of bulbs in the scene, the phases of the electric grid up to city scale, and the light transport matrix. This information yields unmixing of reflections and semi-reflections, nocturnal high dynamic range, and scene rendering with bulbs not observed during...
The images taken through glass often capture a target transmitted scene as well as undesired reflected scenes. In this paper, we propose a low-rank matrix completion algorithm to remove reflection artifacts automatically from multiple glass images taken at slightly different camera locations. We assume that the transmitted scenes are more dominant than the reflected scenes in typical glass images...
We propose a new method for segmenting indoor scenes captured with RGBD or depth cameras with a simple and fast iterative CPU segmentation. The segmentation consists of three main steps. In the first stage, regions grow by adding new pixels based on depth information and normal vectors. Next, multiple regions are merged into bigger surfaces based on adjacency and region statistics. The last stage...
The obstacle detection system could be performed using Pyramidal Lucas Kanade Optical Flow calculation. The calculation is using greyscale images obtained from a camera or video files as input. The results from optical flow calculation then processed into Time to Contact (TTC) value that is used to estimate the distance of the robot to the obstacle. This paper proposed an idea to combine Pyramidal...
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’...
The Microsoft Kinect sensor has been widely used in many applications, but it suffers from the drawback of low depth accuracy. In this paper, we present a unified depth modification model to improve the Kinect depth accuracy by registering depth and color images in an iterative manner. Specifically, in each iteration, we first establish a coarse correspondence based on the feature descriptor of the...
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...
Autonomous robots also known as Unmanned Ground Vehicles (UGV) is of broad and current interest, in both research and industry. Many studies have been done in stereo vision based UGV vision in positive obstacle detection and avoidance, but negative obstacle detection and avoidance remains less explored. In this paper, we propose a new method to detect negative obstacles incorporating the knowledge...
Currently, the only mass-market service robots are floor cleaners and lawn mowers. Although available for more than 20 years, they mostly lack intelligent functions from modern robot research. In particular, the obstacle detection and avoidance is typically a simple physical collision detection. In this work, we discuss a prototype autonomous lawn mower with camera-based non-contact obstacle avoidance...
This paper demonstrates the development of a low cost thermal imaging camera as an alternative to the commercial models. This device consists on a long wave infrared sensor which captures the infrared reflection from the physical objects. Thermal imaging camera technology has provided relevant developments for security systems, being used in surveillance activities such as law-enforcement, home intrusion...
We describe a system for autonomous depth perception for surveillance in real world environments. With the ever-increasing need for surveillance, human operators are facing a challenging task to track suspicious behavior while looking at a large number of videos in real-time. We present an autonomous suspicious object detection method using depth information obtained from the Microsoft Kinect sensor...
The lane marking detection task is an essential process in the field of semi-autonomous and autonomous navigation. This paper proposes a method that combines the color and edge information to robustly detect the lane marking within the image either located far on near to the vehicle. Firstly, the region of interest is extracted from the image. Secondly, the set of lane marking features are extracted...
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