Learning and Matching Multi-View Descriptors for Registration of Point Clouds

Critical to the registration of point clouds is the establishment of a set of accurate correspondences between points in 3D space. The correspondence problem is generally addressed by the design of discriminative 3D local descriptors on the one hand, and the development of robust matching strategies on the other hand. In this work, we first propose a multi-view local descriptor, which is learned from the images of multiple views, for the description of 3D keypoints. Then, we develop a robust matching approach, aiming at rejecting outlier matches based on the efficient inference via belief propagation on the defined graphical model. We have demonstrated the boost of our approaches to registration on the public scanning and multi-view stereo datasets. The superior performance has been verified by the intensive comparisons against a variety of descriptors and matching methods

OCC-VO: Dense Mapping via 3D Occupancy-Based Visual Odometry for Autonomous Driving

Visual Odometry (VO) plays a pivotal role in autonomous systems, with a principal challenge being the lack of depth information in camera images. This paper introduces OCC-VO, a novel framework that capitalizes on recent advances in deep learning to transform 2D camera images into 3D semantic occupancy, thereby circumventing the traditional need for concurrent estimation of ego poses and landmark locations. Within this framework, we utilize the TPV-Former to convert surround view cameras' images into 3D semantic occupancy. Addressing the challenges presented by this transformation, we have specifically tailored a pose estimation and mapping algorithm that incorporates Semantic Label Filter, Dynamic Object Filter, and finally, utilizes Voxel PFilter for maintaining a consistent global semantic map. Evaluations on the Occ3D-nuScenes not only showcase a 20.6% improvement in Success Ratio and a 29.6% enhancement in trajectory accuracy against ORB-SLAM3, but also emphasize our ability to construct a comprehensive map. Our implementation is open-sourced and available at: https://github.com/USTCLH/OCC-VO.Comment: 7pages, 3 figure

Analysis of Neptune's 2017 Bright Equatorial Storm

We report the discovery of a large ($\sim$8500 km diameter) infrared-bright storm at Neptune's equator in June 2017. We tracked the storm over a period of 7 months with high-cadence infrared snapshot imaging, carried out on 14 nights at the 10 meter Keck II telescope and 17 nights at the Shane 120 inch reflector at Lick Observatory. The cloud feature was larger and more persistent than any equatorial clouds seen before on Neptune, remaining intermittently active from at least 10 June to 31 December 2017. Our Keck and Lick observations were augmented by very high-cadence images from the amateur community, which permitted the determination of accurate drift rates for the cloud feature. Its zonal drift speed was variable from 10 June to at least 25 July, but remained a constant $237.4 \pm 0.2$ m s$^{-1}$ from 30 September until at least 15 November. The pressure of the cloud top was determined from radiative transfer calculations to be 0.3-0.6 bar; this value remained constant over the course of the observations. Multiple cloud break-up events, in which a bright cloud band wrapped around Neptune's equator, were observed over the course of our observations. No "dark spot" vortices were seen near the equator in HST imaging on 6 and 7 October. The size and pressure of the storm are consistent with moist convection or a planetary-scale wave as the energy source of convective upwelling, but more modeling is required to determine the driver of this equatorial disturbance as well as the triggers for and dynamics of the observed cloud break-up events.Comment: 42 pages, 14 figures, 6 tables; Accepted to Icaru

Mars Express measurements of surface albedo changes over 2004 - 2010

The pervasive Mars dust is continually transported between the surface and the atmosphere. When on the surface, dust increases the albedo of darker underlying rocks and regolith, which modifies climate energy balance and must be quantified. Remote observation of surface albedo absolute value and albedo change is however complicated by dust itself when lifted in the atmosphere. Here we present a method to calculate and map the bolometric solar hemispherical albedo of the Martian surface using the 2004 - 2010 OMEGA imaging spectrometer dataset. This method takes into account aerosols radiative transfer, surface photometry, and instrumental issues such as registration differences between visible and near-IR detectors. Resulting albedos are on average 17% higher than previous estimates for bright surfaces while similar for dark surfaces. We observed that surface albedo changes occur mostly during the storm season due to isolated events. The main variations are observed during the 2007 global dust storm and during the following year. A wide variety of change timings are detected such as dust deposited and then cleaned over a Martian year, areas modified only during successive global dust storms, and perennial changes over decades. Both similarities and differences with previous global dust storms are observed. While an optically thin layer of bright dust is involved in most changes, this coating turns out to be sufficient to mask underlying mineralogical near-IR spectral signatures. Overall, changes result from apparently erratic events; however, a cyclic evolution emerges for some (but not all) areas over long timescales

Consistent Correspondences for Shape and Image Problems

Establish consistent correspondences between different objects is a classic problem in computer science/vision. It helps to match highly similar objects in both 3D and 2D domain. Inthe 3D domain, finding consistent correspondences has been studying for more than 20 yearsand it is still a hot topic. In 2D domain, consistent correspondences can also help in puzzlesolving. However, only a few works are focused on this approach. In this thesis, we focuson finding consistent correspondences and extend to develop robust matching techniques inboth 3D shape segments and 2D puzzle solving. In the 3D domain, segment-wise matching isan important research problem that supports higher-level understanding of shapes in geometryprocessing. Many existing segment-wise matching techniques assume perfect input segmentation and would suffer from imperfect or over-segmented input. To handle this shortcoming,we propose multi-layer graphs (MLGs) to represent possible arrangements of partially mergedsegments of input shapes. We then adapt the diffusion pruning technique on the MLGs to findconsistent segment-wise matching. To obtain high-quality matching, we develop our own voting step which is able to remove inconsistent results, for finding hierarchically consistent correspondences as final output. We evaluate our technique with both quantitative and qualitativeexperiments on both man-made and deformable shapes. Experimental results demonstrate theeffectiveness of our technique when compared to two state-of-art methods. In the 2D domain,solving jigsaw puzzles is also a classic problem in computer vision with various applications.Over the past decades, many useful approaches have been introduced. Most existing worksuse edge-wise similarity measures for assembling puzzles with square pieces of the same size, and recent work innovates to use the loop constraint to improve efficiency and accuracy. Weobserve that most existing techniques cannot be easily extended to puzzles with rectangularpieces of arbitrary sizes, and no existing loop constraints can be used to model such challenging scenarios. We propose new matching approaches based on sub-edges/corners, modelledusing the MatchLift or diffusion framework to solve square puzzles with cycle consistency.We demonstrate the robustness of our approaches by comparing our methods with state-of-artmethods. We also show how puzzles with rectangular pieces of arbitrary sizes, or puzzles withtriangular and square pieces can be solved by our techniques

System for measuring steel scrap volume using depth imaging

Abstract. Sustainability and green values are major themes in the world today. Companies across all fields are constantly implementing new technologies to reduce emissions and to limit the magnitude of global warming. The steel industry in general is one of the major producers of carbon dioxide emissions. The objective of this thesis was to develop a system to measure the volume of scrap metal being charged to an electric arc furnace. Obtaining the scrap volume would help the furnace operators in timing the charging of scrap baskets, thus avoiding the adverse effects resulting from early and late charging. The intention is to increase the energy efficiency of the process. The theory section of the thesis provides a short overview of the electric arc furnace process and a more detailed description of the charging process. Depth imaging technologies are then explored from a theoretical standpoint to provide the background for the selection and usage of imaging hardware. In this thesis, design science research methodology was utilized to develop the scrap volume measurement system, which consists of imaging hardware and developed software. The actual contribution of this thesis is the algorithm to extract the height of the scrap surface level from a 3-dimensional image of scrap baskets. The development process was iteratively carried out in a steel factory. The system performance was evaluated in a real-world scenario. It was established that the system was able to capture 3-dimensional data from scrap baskets and determine the scrap surface level height according to the algorithm. However, for some cases the image capturing did not perform as expected. These failure cases were a result of either steel dust obstructing the scene or the inability of the camera to capture data from unreflective material. Further research prospects were identified during conducting of the thesis. The failure cases could be addressed either programmatically, with new hardware technology, or a combination of both. Also, research could be conducted on the usage of the information provided by the system in actual charging events with the goal of optimizing charging timing