Active Image-based Modeling with a Toy Drone

Image-based modeling techniques can now generate photo-realistic 3D models from images. But it is up to users to provide high quality images with good coverage and view overlap, which makes the data capturing process tedious and time consuming. We seek to automate data capturing for image-based modeling. The core of our system is an iterative linear method to solve the multi-view stereo (MVS) problem quickly and plan the Next-Best-View (NBV) effectively. Our fast MVS algorithm enables online model reconstruction and quality assessment to determine the NBVs on the fly. We test our system with a toy unmanned aerial vehicle (UAV) in simulated, indoor and outdoor experiments. Results show that our system improves the efficiency of data acquisition and ensures the completeness of the final model.Comment: To be published on International Conference on Robotics and Automation 2018, Brisbane, Australia. Project Page: https://huangrui815.github.io/active-image-based-modeling/ The author's personal page: http://www.sfu.ca/~rha55

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

GASP : Geometric Association with Surface Patches

A fundamental challenge to sensory processing tasks in perception and robotics is the problem of obtaining data associations across views. We present a robust solution for ascertaining potentially dense surface patch (superpixel) associations, requiring just range information. Our approach involves decomposition of a view into regularized surface patches. We represent them as sequences expressing geometry invariantly over their superpixel neighborhoods, as uniquely consistent partial orderings. We match these representations through an optimal sequence comparison metric based on the Damerau-Levenshtein distance - enabling robust association with quadratic complexity (in contrast to hitherto employed joint matching formulations which are NP-complete). The approach is able to perform under wide baselines, heavy rotations, partial overlaps, significant occlusions and sensor noise. The technique does not require any priors -- motion or otherwise, and does not make restrictive assumptions on scene structure and sensor movement. It does not require appearance -- is hence more widely applicable than appearance reliant methods, and invulnerable to related ambiguities such as textureless or aliased content. We present promising qualitative and quantitative results under diverse settings, along with comparatives with popular approaches based on range as well as RGB-D data.Comment: International Conference on 3D Vision, 201

Automated archiving of archaeological aerial images

The main purpose of any aerial photo archive is to allow quick access to images based on content and location. Therefore, next to a description of technical parameters and depicted content, georeferencing of every image is of vital importance. This can be done either by identifying the main photographed object (georeferencing of the image content) or by mapping the center point and/or the outline of the image footprint. The paper proposes a new image archiving workflow. The new pipeline is based on the parameters that are logged by a commercial, but cost-effective GNSS/IMU solution and processed with in-house-developed software. Together, these components allow one to automatically geolocate and rectify the (oblique) aerial images (by a simple planar rectification using the exterior orientation parameters) and to retrieve their footprints with reasonable accuracy, which is automatically stored as a vector file. The data of three test flights were used to determine the accuracy of the device, which turned out to be better than 1° for roll and pitch (mean between 0.0 and 0.21 with a standard deviation of 0.17–0.46) and better than 2.5° for yaw angles (mean between 0.0 and −0.14 with a standard deviation of 0.58–0.94). This turned out to be sufficient to enable a fast and almost automatic GIS-based archiving of all of the imagery