Acquisition of 3D shapes of moving objects using fringe projection profilometry

Three-dimensional (3D) shape measurement for object surface reconstruction has potential applications in many areas, such as security, manufacturing and entertainment. As an effective non-contact technique for 3D shape measurements, fringe projection profilometry (FPP) has attracted significant research interests because of its high measurement speed, high measurement accuracy and ease to implement. Conventional FPP analysis approaches are applicable to the calculation of phase differences for static objects. However, 3D shape measurement for dynamic objects remains a challenging task, although they are highly demanded in many applications. The study of this thesis work aims to enhance the measurement accuracy of the FPP techniques for the 3D shape of objects subject to movement in the 3D space. The 3D movement of objects changes not only the position of the object but also the height information with respect to the measurement system, resulting in motion-induced errors with the use of existing FPP technology. The thesis presents the work conducted for solutions of this challenging problem

Multi-view dynamic scene modeling

Modeling dynamic scenes/events from multiple fixed-location vision sensors, such as video camcorders, infrared cameras, Time-of-Flight sensors etc, is of broad interest in computer vision society, with many applications including 3D TV, virtual reality, medical surgery, markerless motion capture, video games, and security surveillance. However, most of the existing multi-view systems are set up in a strictly controlled indoor environment, with fixed lighting conditions and simple background views. Many challenges are preventing the technology to an outdoor natural environment. These include varying sunlight, shadows, reflections, background motion and visual occlusion. In this thesis, I address different aspects to overcome all of the aforementioned difficulties, so as to reduce human preparation and manipulation, and to make a robust outdoor system as automatic as possible. In particular, the main novel technical contributions of this thesis are as follows: a generic heterogeneous sensor fusion framework for robust 3D shape estimation together; a way to automatically recover 3D shapes of static occluder from dynamic object silhouette cues, which explicitly models the static visual occluding event along the viewing rays; a system to model multiple dynamic objects shapes and track their identities simultaneously, which explicitly models the inter-occluding event between dynamic objects; a scheme to recover an object's dense 3D motion flow over time, without assuming any prior knowledge of the underlying structure of the dynamic object being modeled, which helps to enforce temporal consistency of natural motions and initializes more advanced shape learning and motion analysis. A unified automatic calibration algorithm for the heterogeneous network of conventional cameras/camcorders and new Time-of-Flight sensors is also proposed

Intrinsic Images and their Applications in Intelligent Systems

The overall goal of the thesis is to research intelligent systems and to provide one more innovative piece in the puzzle towards general artificial intelligence. Because one quickly realizes the importance of computer vision for this endeavor, and in there specifically the need to understand the 3D world through their 2D projections into images, we thoroughly investigate the field of intrinsic images in this thesis and improve the intrinsic decomposition of arbitrary images to enable smarter intelligent systems. We demonstrate the utilization of such a decomposition in the task of relighting, where the intrinsic structure is shown to improve results

Quality Characterization of Tissue and Newsprint Paper based on Image Measurements; Possibilities of On-line Imaging

The paper industry is at a turning point worldwide. The consumption of printed products is assumed to decrease significantly because of electronic gadgets and the internet. Furthermore, the importance of forests and woods in the global warming issue is significant and causes limitations to papermakers to produce cheap products. However at the same time the end users demand high quality products at reasonable prices. Therefore, the cost-efficiency in papermaking process will play a more significant role in the future. This thesis proposes a set of image analyses and methods which can be implemented in present on-line imaging systems, without a massive effort. The imaging systems can measure the paper accurately and in a versatile manner which improves the control of the paper machine and thus enhances the cost efficiency of the papermaking process. The creping process which generates the wavy microstructure to tissue paper - a creping pattern - mainly determines the quality properties of the tissue paper. This thesis applied the photometric stereo method with 2D spectral analysis to characterize the versatile properties of creping pattern. The creping process also affects the free fiber ends and pinholes in tissue paper. The free fiber end detection method was based on the number of shadows of fibers. The shadows were made visible by removing the creping pattern from the images of tissue paper with photometric stereo method. The pinhole detection method was based on the linearly polarized light transmitted through paper and the camera with rotating polarizer. It is anticipated based on the thesis that the characteristics of creping patterns and the number of pinholes are possible to be measured on-line by using existing imaging technology in paper machines. The web inspection systems installed on paper machines measure the web-wide light transmittance of paper. At present they detect and classify defects such as holes and dirt particles and estimate some simple paper characteristics such as light transmittance and formation. This thesis proposed methods to utilize the on-line transmittance images more versatile in newsprint grade. The cross directional shrinkage profile and the small scale structural characteristics such as the light transmittance, formation, length scale of formation and orientation parameters of paper were estimated based on the statistical measures and the features of frequency distribution in the 2D spectrum. The uncertainty of basis weight estimate approximated from the transmittance images was studied with correlation analysis and the Kubelka-Munk equations. It was noticed that the initial quality of the on-line images was insufficient for evaluating formation characteristics and basis weight reliably. However capturing a complete set of calibration and reference images will also enable the formation and basis weight estimation of paper and thus increasing the value of web inspection system significantly

Analysis, Modeling and Dynamic Optimization of 3D Time-of-Flight Imaging Systems

The present thesis is concerned with the optimization of 3D Time-of-Flight (ToF) imaging systems. These novel cameras determine range images by actively illuminating a scene and measuring the time until the backscattered light is detected. Depth maps are constructed from multiple raw images. Usually two of such raw images are acquired simultaneously using special correlating sensors. This thesis covers four main contributions: A physical sensor model is presented which enables the analysis and optimization of the process of raw image acquisition. This model supports the proposal of a new ToF sensor design which employs a logarithmic photo response. Due to asymmetries of the two read-out paths current systems need to acquire the raw images in multiple instances. This allows the correction of systematic errors. The present thesis proposes a method for dynamic calibration and compensation of these asymmetries. It facilitates the computation of two depth maps from a single set of raw images and thus increases the frame rate by a factor of two. Since not all required raw images are captured simultaneously motion artifacts can occur. The present thesis proposes a robust method for detection and correction of such artifacts. All proposed algorithms have a computational complexity which allowsreal-time execution even on systems with limited resources (e.g. embeddedsystems). The algorithms are demonstrated by use of a commercial ToF camera