Efficient Model-based 3D Tracking by Using Direct Image Registration

This thesis deals with the problem of efficiently tracking 3D objects in sequences of images. We tackle the efficient 3D tracking problem by using direct image registration. This problem is posed as an iterative optimization procedure that minimizes a brightness error norm. We review the most popular iterative methods for image registration in the literature, turning our attention to those algorithms that use efficient optimization techniques. Two forms of efficient registration algorithms are investigated. The first type comprises the additive registration algorithms: these algorithms incrementally compute the motion parameters by linearly approximating the brightness error function. We centre our attention on Hager and Belhumeur’s factorization-based algorithm for image registration. We propose a fundamental requirement that factorization-based algorithms must satisfy to guarantee good convergence, and introduce a systematic procedure that automatically computes the factorization. Finally, we also bring out two warp functions to register rigid and nonrigid 3D targets that satisfy the requirement. The second type comprises the compositional registration algorithms, where the brightness function error is written by using function composition. We study the current approaches to compositional image alignment, and we emphasize the importance of the Inverse Compositional method, which is known to be the most efficient image registration algorithm. We introduce a new algorithm, the Efficient Forward Compositional image registration: this algorithm avoids the necessity of inverting the warping function, and provides a new interpretation of the working mechanisms of the inverse compositional alignment. By using this information, we propose two fundamental requirements that guarantee the convergence of compositional image registration methods. Finally, we support our claims by using extensive experimental testing with synthetic and real-world data. We propose a distinction between image registration and tracking when using efficient algorithms. We show that, depending whether the fundamental requirements are hold, some efficient algorithms are eligible for image registration but not for tracking.

Mechanical behavior and failure micromechanisms of hybrid 3D woven composites in tension

The deformation and failure micromechanisms of a hybrid 3D woven composite were studied in tension. Plain and open-hole composite coupons were tested in tension until failure in the fill and warp directions, as well as fiber tows extracted from the dry fabric and impregnated with the matrix. The macroscopic evolution of damage in the composite coupons was assessed by means of periodic unloading–reloading (to obtain the elastic modulus and the residual strain), whereas the microscopic mechanism were established by means of X-ray computed microtomography. To this end, specimens were periodically removed from the mechanical testing machine and infiltrated with ZnI-containing liquid to assess the main damage modes as a function of the applied strain. The experimental observations and the predictions of an isostrain model were used to understand the key factors controlling the elastic modulus, strength and notch sensitivity of hybrid 3D woven composites in tension. It was found that the full contribution of the glass fibers to the composite strength was not employed, due to the premature fracture of the carbon fibers, but their presence increased the fracture strain and the energy dissipated during fracture. Thus, hybridization of the 3D woven composite led to a notch-insensitive behavior as demonstrated by open-hole tests