Tracking human motion with multiple cameras using articulated ICP with hard constraints

Questa tesi propone un nuovo algoritmo basato su ICP per il tracking di un modello scheletrico articolato di un corpo umano. L\u2019algoritmo proposto prende in input immagini calibrate di un soggetto, calcola la ricostruzione volumetrica e la linea mediale del corpo e quindi posiziona in modo adeguato il modello, composto di segmenti, in ogni frame usando una versione di ICP modificata (versione che usa una strategia di attraversamento alberi gerarchica che mantiene connessi tutti i segmenti del modello nei giunti relativi). L\u2019approccio proposto usa limiti cinematica per i giunti e un filtro di Kalman esteso per fare il tracking del modello. Il primo contributo originale di questa tesi \ue8 l\u2019algoritmo per trovare i punti sullo scheletro di un volume tridimensionale. L\u2019algoritmo, usando una tecnica di slicing trova l\u2019asse mediale di un volume 3D in modo veloce utilizzando il processore della scheda grafica e le texture units della scheda stessa. Questo algoritmo produce ottimi risultati per quanto riguarda la qualit\ue0 e le prestazioni se comparato con altri algoritmi in letteratura. Un altro contributo originale \ue8 l\u2019introduzione di una nuova strategia di tracking basata su un approccio gerarchico dell\u2019algoritmo ICP, utilizzato per trovare le congruenze tra un modello di corpo umano composto da soli segmenti e un insieme di punti 3D. L\u2019algoritmo usa una versione di ICP dove tutti i punti 3D sono pesati in funzione del segmento del corpo preso in considerazione dall\u2019algoritmo in quel momento. L\u2019applicazione di queste tecniche dimostra la bont\ue0 del metodo e le prestazioni ottenute in termini di qualit\ue0 della stima della posa sono comparabili con altri lavori in letteratura. I risultati presentati nella tesi dimostrano la fattibilit\ue0 dell\u2019approccio generale, che si intende utilizzare in un sistema completo per il tracking di corpi umani senza l\u2019uso di marcatori. In futuro il lavoro pu\uf2 essere esteso ottimizzando l\u2019implementazione e la codifica in modo da poter ottenere prestazioni real-time.This thesis proposed a new ICP-based algorithm for tracking articulated skeletal model of a human body. The proposed algorithm takes as input multiple calibrated views of the subject, computes a volumetric reconstruction and the centerlines of the body and fits the skeletal body model in each frame using a hierarchic tree traversal version of the ICP algorithm that preserves the connection of the segments at the joints. The proposed approach uses the kinematic constraints and an Extended Kalman Filter to track the body pose. The first contribution is a new algorithm to find the skeletal points of a 3D volume. The algorithm using a slicing technique find the medial axis of a volume in a fast way using the graphic card processor and the texture units. This algorithm produce good results in quality and performance compared to other works in literature. Another contribution is the introduction of a new tracking strategy based on a hierarchical application of the ICP standard algorithm to find the match between a stick body model and a set of 3D points. The algorithm use a traversing version of ICP where also all the 3D points are weighted in such a way every limbs of the model can best fit on the right portion of the body. The application of these techniques shown the feasibility of the method and the performances obtained in terms of quality of estimate pose are comparable with other works in literature. The results presented here demonstrate the feasibility of the approach, which is is intended to be used in complete system for vision-based markerless human body tracking. Future work will aimed at optimizing the implementation, in order to achieve real-time performances

The development of a hybrid virtual reality/video view-morphing display system for teleoperation and teleconferencing

Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2000.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 84-89).The goal of this study is to extend the desktop panoramic static image viewer concept (e.g., Apple QuickTime VR; IPIX) to support immersive real time viewing, so that an observer wearing a head-mounted display can make free head movements while viewing dynamic scenes rendered in real time stereo using video data obtained from a set of fixed cameras. Computational experiments by Seitz and others have demonstrated the feasibility of morphing image pairs to render stereo scenes from novel, virtual viewpoints. The user can interact both with morphed real world video images, and supplementary artificial virtual objects (“Augmented Reality”). The inherent congruence of the real and artificial coordinate frames of this system reduces registration errors commonly found in Augmented Reality applications. In addition, the user’s eyepoint is computed locally so that any scene lag resulting from head movement will be less than those from alternative technologies using remotely controlled ground cameras. For space applications, this can significantly reduce the apparent lag due to satellite communication delay. This hybrid VR/view-morphing display (“Virtual Video”) has many important NASA applications including remote teleoperation, crew onboard training, private family and medical teleconferencing, and telemedicine. The technical objective of this study developed a proof-of-concept system using a 3D graphics PC workstation of one of the component technologies, Immersive Omnidirectional Video, of Virtual Video. The management goal identified a system process for planning, managing, and tracking the integration, test and validation of this phased, 3-year multi-university research and development program.by William E. Hutchison.S.M

Affine Invariant Detection of Periodic Motion

Current approaches for detecting periodic motion assume a stationary camera and place limits on an object's motion. These approaches rely on the assumption that a periodic motion projects to a set of periodic image curves, an assumption that is invalid in general. Using affine-invariance, we derive necessary and sufficient conditions for an image sequence to be the projection of a periodic motion. No restrictions are placed on either the motion of the camera or the object. Our algorithm is shown to be provably-correct for noise-free data and is extended to be robust with respect to occlusions and noise. The extended algorithm is evaluated with real and synthetic image sequences