Optimal Hardware and Software Design of an Image-Based System for Capturing Dynamic Movements

In contrast to conventional image-capture systems, which attempt to minimize the amount of data collected during capture, typically by using hardware filters, the more general condition of using all information captured on a camera sensor is much more challenging and requires rigorous consideration of the hardware and software pipelines to obtain accurate tracking results. In this paper, this issue is specifically addressed by describing a unique hardware and software design implemented for use as a fully image-based capture system. An attempt is made to minimize the cost of this system by maximizing hardware control through software implementation. The hardware and software requirements are described in the context of the desired highspeed capture suitable for earthquake motions or other dynamic movements in a scene. Experiments are conducted and presented illustrating the good performance and stability of the system. This system is deemed suitable for the general condition of a building interior

Image enhancement from a stabilised video sequence

The aim of video stabilisation is to create a new video sequence where the motions (i.e. rotations, translations) and scale differences between frames (or parts of a frame) have effectively been removed. These stabilisation effects can be obtained via digital video processing techniques which use the information extracted from the video sequence itself, with no need for additional hardware or knowledge about camera physical motion. A video sequence usually contains a large overlap between successive frames, and regions of the same scene are sampled at different positions. In this paper, this multiple sampling is combined to achieve images with a higher spatial resolution. Higher resolution imagery play an important role in assisting in the identification of people, vehicles, structures or objects of interest captured by surveillance cameras or by video cameras used in face recognition, traffic monitoring, traffic law reinforcement, driver assistance and automatic vehicle guidance systems

Shape and deformation measurement using heterodyne range imaging technology

Range imaging is emerging as a promising alternative technology for applications that require non-contact visual inspection of object deformation and shape. Previously, we presented a solid-state full-field heterodyne range imaging device capable of capturing three-dimensional images with sub-millimetre range resolution. Using a heterodyne indirect time-of-flight configuration, this system simultaneously measures distance (and intensity), for each pixel in a cameras field of view. In this paper we briefly describe our range imaging system, and its principle of operation. By performing measurements on several metal objects, we demonstrate the potential capabilities of this technology for surface profiling and deformation measurement. In addition to verifying system performance, the reported examples highlight some important system limitations. With these in mind we subsequently discuss the further developments required to enable the use of this device as a robust and practical tool in non-destructive testing and measurement applications

Neo: Virtual Object Modeling using Commodity Hardware

Recent developments in augmented reality technology have paved way for newapplications in a wide range of areas. These include the commercial markets,medicine applications, military applications and education. The technology pro-vides immersive images to enhance our perception of the world. Augmentedreality addresses challenges related to problem-solving by seamlessly integrat-ing digital images into real-world images.In the context of construction and maintenance industry, project inspections canbe time-consuming and tedious. These inspections involve usages of expensiveand specialized hardware. Some inspections even use physical blueprints anddrawings along with standardized measurement tools. This approach can posepractical challenges and be prone to errors.In this thesis we present Neo, a surface reconstruction system on commodityhardware. It utilizes augmented reality technology by scanning physical sur-roundings and reconstructs them as virtual objects. They are displayed on topof the camera’s live preview of the real world. By using a pipeline architecturewe model the physical surroundings in terms of their shapes and visual appear-ances. Cyber-physical information about the reconstructed virtual models areannotated in real-time. Evaluations of the system show us potentials to createrealistic copies of physical object

INTELLIGENT COMPUTER VISION SYSTEM FOR SCORE DETECTION IN BASKETBALL

Development of an intelligent computer vision system for Smart IoT basketball training and entertainment includes the development of a range of various subsystems, where score detection subsystem is playing a crucial role. This paper proposes the architecture of such a score detection subsystem to improve reliability and accuracy of the RFID technology used primarily for verification purposes. Challenges encompass both hardware-software interdependencies, optimal camera selection, and cost-effectiveness considerations. Leveraging machine learning algorithms, the vision-based subsystem aims not only to detect scores but also to facilitate online video streaming. Although the use of multiple cameras offers expanded field coverage and heightened precision, it concurrently introduces technical intricacies and increased costs due to image fusion and escalated processing requirements. This research navigates the intricate balance between achieving precise score detection and pragmatic system development. Through precise camera configuration optimization, the proposed system harmonizes hardware and software components