Visual motion : algorithms for analysis and application

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1990.Includes bibliographical references (leaves 71-73).by Michael Adam Sokolov.M.S

A Variational Framework for Structure from Motion inOmnidirectional Image Sequences

We address the problem of depth and ego-motion estimation from omnidirectional images. We propose a correspondence-free structure-from-motion problem for sequences of images mapped on the 2-sphere. A novel graph-based variational framework is first proposed for depth estimation between pairs of images. The estimation is cast as a TV-L1 optimization problem that is solved by a fast graph-based algorithm. The ego-motion is then estimated directly from the depth information without explicit computation of the optical flow. Both problems are finally addressed together in an iterative algorithm that alternates between depth and ego-motion estimation for fast computation of 3D information from motion in image sequences. Experimental results demonstrate the effective performance of the proposed algorithm for 3D reconstruction from synthetic and natural omnidirectional image

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Flow networks: A characterization of geophysical fluid transport

We represent transport between different regions of a fluid domain by flow networks, constructed from the discrete representation of the Perron-Frobenius or transfer operator associated to the fluid advection dynamics. The procedure is useful to analyze fluid dynamics in geophysical contexts, as illustrated by the construction of a flow network associated to the surface circulation in the Mediterranean sea. We use network-theory tools to analyze the flow network and gain insights into transport processes. In particular we quantitatively relate dispersion and mixing characteristics, classically quantified by Lyapunov exponents, to the degree of the network nodes. A family of network entropies is defined from the network adjacency matrix, and related to the statistics of stretching in the fluid, in particular to the Lyapunov exponent field. Finally we use a network community detection algorithm, Infomap, to partition the Mediterranean network into coherent regions, i.e. areas internally well mixed, but with little fluid interchange between them.Comment: 16 pages, 15 figures. v2: published versio

Statistical extraction of process zones and representative subspaces in fracture of random composite

We propose to identify process zones in heterogeneous materials by tailored statistical tools. The process zone is redefined as the part of the structure where the random process cannot be correctly approximated in a low-dimensional deterministic space. Such a low-dimensional space is obtained by a spectral analysis performed on pre-computed solution samples. A greedy algorithm is proposed to identify both process zone and low-dimensional representative subspace for the solution in the complementary region. In addition to the novelty of the tools proposed in this paper for the analysis of localised phenomena, we show that the reduced space generated by the method is a valid basis for the construction of a reduced order model.Comment: Submitted for publication in International Journal for Multiscale Computational Engineerin

Object-based 3-d motion and structure analysis for video coding applications

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1997.Thesis (Ph.D.) -- -Bilkent University, 1997.Includes bibliographical references leaves 102-115Novel 3-D motion analysis tools, which can be used in object-based video codecs, are proposed. In these tools, the movements of the objects, which are observed through 2-D video frames, are modeled in 3-D space. Segmentation of 2-D frames into objects and 2-D dense motion vectors for each object are necessary as inputs for the proposed 3-D analysis. 2-D motion-based object segmentation is obtained by Gibbs formulation; the initialization is achieved by using a fast graph-theory based region segmentation algorithm which is further improved to utilize the motion information. Moreover, the same Gibbs formulation gives the needed dense 2-D motion vector field. The formulations for the 3-D motion models are given for both rigid and non- rigid moving objects. Deformable motion is modeled by a Markov random field which permits elastic relations between neighbors, whereas, rigid 3-D motion parameters are estimated using the E-matrix method. Some improvements on the E-matrix method are proposed to make this algorithm more robust to gross errors like the consequence of incorrect segmentation of 2-D correspondences between frames. Two algorithms are proposed to obtain dense depth estimates, which are robust to input errors and suitable for encoding, respectively. While the former of these two algorithms gives simply a MAP estimate, the latter uses rate-distortion theory. Finally, 3-D motion models are further utilized for occlusion detection and motion compensated temporal interpolation, and it is observed that for both applications 3-D motion models have superiority over their 2-D counterparts. Simulation results on artificial and real data show the advantages of the 3-D motion models in object-based video coding algorithms.Alatan, A AydinPh.D

Filtering of image sequences: on line edge detection and motion reconstruction

L'argomento della Tesi riguarda líelaborazione di sequenze di immagini, relative ad una scena in cui uno o pi˘ oggetti (possibilmente deformabili) si muovono e acquisite da un opportuno strumento di misura. A causa del processo di misura, le immagini sono corrotte da un livello di degradazione. Si riporta la formalizzazione matematica dellíinsieme delle immagini considerate, dellíinsieme dei moti ammissibili e della degradazione introdotta dallo strumento di misura. Ogni immagine della sequenza acquisita ha una relazione con tutte le altre, stabilita dalla legge del moto della scena. Líidea proposta in questa Tesi Ë quella di sfruttare questa relazione tra le diverse immagini della sequenza per ricostruire grandezze di interesse che caratterizzano la scena. Nel caso in cui si conosce il moto, líinteresse Ë quello di ricostruire i contorni dellíimmagine iniziale (che poi possono essere propagati attraverso la stessa legge del moto, in modo da ricostruire i contorni della generica immagine appartenente alla sequenza in esame), stimando líampiezza e del salto del livello di grigio e la relativa localizzazione. Nel caso duale si suppone invece di conoscere la disposizione dei contorni nellíimmagine iniziale e di avere un modello stocastico che descriva il moto; líobiettivo Ë quindi stimare i parametri che caratterizzano tale modello. Infine, si presentano i risultati dellíapplicazione delle due metodologie succitate a dati reali ottenuti in ambito biomedicale da uno strumento denominato pupillometro. Tali risultati sono di elevato interesse nellíottica di utilizzare il suddetto strumento a fini diagnostici