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Autonomous robots require accurate localizations and dense mappings for motion planning. We consider the navigation scenario where the dense representation of the robot surrounding must be immediately available, and require that the system is capable of an instantaneous map correction if a loop closure is detected by the localization module. To satisfy the real‐time processing requirement of online...
Autonomous navigation, which consists of a systematic integration of localization, mapping, motion planning and control, is the core capability of mobile robotic systems. However, most research considers only isolated technical modules. There exist significant gaps between maps generated by SLAM algorithms and maps required for motion planning. This paper presents a complete online system that consists...
We propose a novel edge-based visual–inertial fusion approach to address the problem of tracking aggressive motions with real-time state estimates. At the front-end, our system performs edge alignment, which estimates the relative poses in the distance transform domain with a larger convergence basin and stronger resistance to changing lighting conditions or camera exposures compared to the popular...
Stereo cameras and dense stereo matching algorithms are core components for many robotic applications due to their abilities to directly obtain dense depth measurements and their robustness against changes in lighting conditions. However, the performance of dense depth estimation relies heavily on accurate stereo extrinsic calibration. In this work, we present a real-time markerless approach for obtaining...
In this work, we address the problem of aggressive flight of a quadrotor aerial vehicle using cameras and IMUs as the only sensing modalities. We present a fully integrated quadrotor system and demonstrate through online experiment the capability of autonomous flight with linear velocities up to 4.2 m/s, linear accelerations up to 9.6 m/s2, and angular velocities up to 245.1 degree/s. Central to our...
We propose a sliding window-based dense visual-inertial fusion method for real-time tracking of challenging aggressive motions. Our method combines recent advances in direct dense visual odometry, inertial measurement unit (IMU) preintegration, and graph-based optimization. At the front-end, direct dense visual odometry provides camera pose tracking that is resistant to motion blur. At the back-end,...
Image colorization aims to add colors to grayscale images, which used to be a time-consuming and tedious task that requires lots of human efforts. In this paper, we present a novel colorization method based on color propagation and rank minimization. Given a small portion of chrominance values and a grayscale image, we firstly propagate the known color values to other pixels to be colorized. As the...
In this work, we tackle the problem of coloring black-and-white images, which is image colorization. Existing image colorization algorithms can be categorized into two types: scribble-based colorization algorithms and example-based colorization algorithms. Differently, we propose a hybrid scheme that combines the advantages of both categories. Given the grayscale image to be colorized and a few color...
Digital image matting is the determination of foreground color, background color, and an opacity value of each pixel for an input image. Inherently, matting is a highly ill-posed and under-constrained problem. Thus, some assumptions need to be made to resolve it. Inspired by closed-form matting and color clustering matting, in this work, we first develop an adaptive sample clustering criterion to...
The High Efficiency Video Coding (HEVC) utilizes Z-scan order to process coding units (CUs). For intra prediction, this order cannot fully exploit the spatial correlation between adjacent CUs. After transform and quantization, the residue still contains lots of energy along edges which consumes many bits for compression. To effectively reduce the residue energy along edges, a novel intra prediction...
The advancing digital photography technology has resulted in a large number of photos stored in personal computers. Photo album compression algorithms aim to save storage space and efficiently manage photos. In this paper, a general forest structure model involving depth constrain for photo album compression is proposed, which further exploits the correlations between images in the photo album. We...
Subpixel-based image downsampling is attractive in that it produces higher apparent resolution of down-sampled images on LCD displays. However increased luminance resolution is achieved at the price of color fringing artifacts. In this paper, we propose an algorithm to find a pleasing balance between increased resolution and color fidelity. We separate the subpixel-based downsampling into two stages,...
Subpixel-based image down-sampling is a class of methods that can provide improved apparent resolution of the down-scaled image compared to the pixel-based methods. The frequency characteristics of all possible subpixel-based down-sampling patterns for RGB vertical stripes are analytically studied in this paper. Our proposed algorithm reveals that there are merely seven equivalent energy distributions...
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