Single-Shot Direct Block Address Encoding for Learning Screen Geometry

3D surface reconstruction has many applications in different domains such as projection mapping, virtual reality, robot navigation, human computer interaction and manufacturing inspection, to name a few. Among different methods of 3D reconstruction, structured light is widely used as it is comparatively cheap and accessible and solves the main problem of traditional stereo vision systems which is finding accurate pixel correspondences between two or multiple views. Structured light techniques can be most fundamentally categorized in terms of the number of projected images over time, whether a single image (single-shot) or multiple images (multi-shot). Multi-shot structured light methods take advantage of multiple images that are projected sequentially over time, allowing simple encoding / decoding of projector pixel addresses. In contrast, single-shot structured light is preferred in contexts of dynamically moving cameras, projectors or surfaces, and in scenarios where short projection time is important. In this thesis, a new framework for designing single-shot structured light images using tag embedding, called Direct Block Address Encoding, is presented which, unlike previous methods, results in efficient encoding, decoding and 3D reconstruction. Also, error detection and correction mechanisms are designed to detect pixel codewords with errors and find their correspondences in the projector image. In addition, the relationship between different design parameters (alphabet size, encoding Scheme, tag size, block size) are derived to cover projectors with different resolutions. Experimental results demonstrate that the proposed scheme is capable of obtaining projector-camera pixel correspondences at higher speed in comparison with previous tag embedding methods, allowing for learning screen geometry from a single shot with high resolution projectors and dynamic cameras and projectors. The proposed Direct Block Address Encoding scheme offers 2-3 times speed up for 3D reconstruction and 5-6 times speed up for encoding/decoding stages due to not requiring a look-up table and/or an exhaustive search, something not achieved with other methods

Rectification Based Single-Shot Structured Light for Accurate and Dense 3D Reconstruction

Structured Light (SL) patterns generated based on pseudo-random arrays are widely used for single-shot 3D reconstruction using projector-camera systems. These SL images consist of a set of tags with different appearances, where these patterns will be projected on a target surface, then captured by a camera and decoded. The precision of localizing these tags from captured camera images affects the quality of the pixel-correspondences between the projector and the camera, and consequently that of the derived 3D shape. In this paper, we incorporate a quadrilateral representation for the detected SL tags that allows the construction of robust and accurate pixel-correspondences and the application of a spatial rectification module that leads to high tag classification accuracy. When applying the proposed method to single-shot 3D reconstruction, we show the effectiveness of this method over a baseline in estimating denser and more accurate 3D point-clouds

Autonomous inspection and construction of civil infrastructure using robots

With rapid population growth worldwide, there is a high demand for new construction and inspection of civil structures, which is challenged by skilled worker shortage, and by inefficient and expensive manual construction and inspection practices. Therefore, it is imperative to develop faster, more economical, and sustainable construction and inspection methods. In recent years, robotic technologies have gained attraction in automating the construction and inspection process. Modular construction using robots has shown great potential in replacing the traditional design, fabrication, and construction to the next industry standard, where higher quality control, precision design, economical transportation, faster on-site construction, less material waste, less site disturbance, and higher utilization of construction material can be achieved. Robot-aided inspection using various types of sensing and control units has shown promising results in replacing traditional manual inspection, which can reduce the cost, and improve efficiency and consistency. In this chapter, the current development of robot-aided construction and inspection methods is first reviewed. Then, a detailed methodology for robotic construction and inspection is described to provide a theoretical basis. Finally, to further demonstrate the applicability of robots in automated construction and inspection, three case studies, including automatic construction using mobile cranes, and autonomous inspection using micro aerial vehicles (MAVs) and unmanned ground vehicles (UGVs), are presented. The results indicate that the use of robots with other appropriate control and sensing units can successfully achieve different desired tasks such as autonomous navigation, mapping, construction, and inspection of civil structures

The role of SF3B1 and NOTCH1 in the pathogenesis of leukemia

The discovery of new genes/pathways improves our knowledge of cancer pathogenesis and presents novel potential therapeutic options. For instance, splicing factor 3b subunit 1 (SF3B1) and NOTCH1 genetic alterations have been identified at a high frequency in hematological malignancies, such as leukemia, and may be related to the prognosis of involved patients because they change the nature of malignancies in different ways like mediating therapeutic resistance; therefore, studying these gene/pathways is essential. This review aims to discuss SF3B1 and NOTCH1 roles in the pathogenesis of various types of leukemia and the therapeutic potential of targeting these genes or their mutations to provide a foundation for leukemia treatment