8 research outputs found
Interaktive Raumzeitrekonstruktion in der Computergraphik
High-quality dense spatial and/or temporal reconstructions and correspondence maps from camera images, be it optical flow, stereo or scene flow, are an essential prerequisite for a multitude of computer vision and graphics tasks, e.g. scene editing or view interpolation in visual media production.
Due to the ill-posed nature of the estimation problem in typical setups (i.e. limited amount of cameras, limited frame rate), automated estimation approaches are prone to erroneous correspondences and subsequent quality degradation in many non-trivial cases such as occlusions, ambiguous movements, long displacements, or low texture.
While improving estimation algorithms is one obvious possible direction, this thesis complementarily concerns itself with creating intuitive, high-level user interactions that lead to improved correspondence maps and scene reconstructions.
Where visually convincing results are essential, rendering artifacts resulting from estimation errors are usually repaired by hand with image editing tools, which is time consuming and therefore costly. My new user interactions, which integrate human scene recognition capabilities to guide a semi-automatic correspondence or scene reconstruction algorithm, save considerable effort and enable faster and more efficient production of visually convincing rendered images.Raumzeit-Rekonstruktion in Form von dichten rĂ€umlichen und/oder zeitlichen Korrespondenzen zwischen Kamerabildern, sei es optischer Fluss, Stereo oder Szenenfluss, ist eine wesentliche Voraussetzung fĂŒr eine Vielzahl von Aufgaben in der Computergraphik, zum Beispiel zum Editieren von Szenen oder Bildinterpolation.
Da sowohl die Anzahl der Kameras als auch die Bildfrequenz begrenzt sind, ist das Rekonstruktionsproblem unterbestimmt, weswegen automatisierte SchĂ€tzungen hĂ€ufig fehlerhafte Korrespondenzen fĂŒr nichttriviale FĂ€lle wie Verdeckungen, mehrdeutige oder groĂe Bewegungen, oder einheitliche Texturen enthalten; jede Bildsynthese basierend auf den partiell falschen SchĂ€tzungen muĂ daher QualitĂ€tseinbuĂen in Kauf nehmen.
Man kann nun zum einen versuchen, die SchÀtzungsalgorithmen zu verbessern. KomplementÀr dazu kann man möglichst effiziente Interaktionsmöglichkeiten entwickeln, die die QualitÀt der Rekonstruktion drastisch verbessern. Dies ist das Ziel dieser Dissertation.
FĂŒr visuell ĂŒberzeugende Resultate mĂŒssen Bildsynthesefehler bislang manuell in einem aufwĂ€ndigen Nachbearbeitungsschritt mit Hilfe von Bildbearbeitungswerkzeugen korrigiert werden. Meine neuen Benutzerinteraktionen, welche menschliches SzenenverstĂ€ndnis in halbautomatische Algorithmen integrieren, verringern den Nachbearbeitungsaufwand betrĂ€chtlich und ermöglichen so eine schnellere und effizientere Produktion qualitativ hochwertiger synthetisierter Bilder
Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics
This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ⌠7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p
Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm
Abstractâ Online transportation has become a basic
requirement of the general public in support of all activities to go
to work, school or vacation to the sights. Public transportation
services compete to provide the best service so that consumers
feel comfortable using the services offered, so that all activities
are noticed, one of them is the search for the shortest route in
picking the buyer or delivering to the destination. Node
Combination method can minimize memory usage and this
methode is more optimal when compared to A* and Ant Colony
in the shortest route search like Dijkstra algorithm, but canât
store the history node that has been passed. Therefore, using
node combination algorithm is very good in searching the
shortest distance is not the shortest route. This paper is
structured to modify the node combination algorithm to solve the
problem of finding the shortest route at the dynamic location
obtained from the transport fleet by displaying the nodes that
have the shortest distance and will be implemented in the
geographic information system in the form of map to facilitate
the use of the system.
Keywordsâ Shortest Path, Algorithm Dijkstra, Node
Combination, Dynamic Location (key words
Head-Driven Phrase Structure Grammar
Head-Driven Phrase Structure Grammar (HPSG) is a constraint-based or declarative approach to linguistic knowledge, which analyses all descriptive levels (phonology, morphology, syntax, semantics, pragmatics) with feature value pairs, structure sharing, and relational constraints. In syntax it assumes that expressions have a single relatively simple constituent structure. This volume provides a state-of-the-art introduction to the framework. Various chapters discuss basic assumptions and formal foundations, describe the evolution of the framework, and go into the details of the main syntactic phenomena. Further chapters are devoted to non-syntactic levels of description. The book also considers related fields and research areas (gesture, sign languages, computational linguistics) and includes chapters comparing HPSG with other frameworks (Lexical Functional Grammar, Categorial Grammar, Construction Grammar, Dependency Grammar, and Minimalism)
Head-Driven Phrase Structure Grammar
Head-Driven Phrase Structure Grammar (HPSG) is a constraint-based or declarative approach to linguistic knowledge, which analyses all descriptive levels (phonology, morphology, syntax, semantics, pragmatics) with feature value pairs, structure sharing, and relational constraints. In syntax it assumes that expressions have a single relatively simple constituent structure. This volume provides a state-of-the-art introduction to the framework. Various chapters discuss basic assumptions and formal foundations, describe the evolution of the framework, and go into the details of the main syntactic phenomena. Further chapters are devoted to non-syntactic levels of description. The book also considers related fields and research areas (gesture, sign languages, computational linguistics) and includes chapters comparing HPSG with other frameworks (Lexical Functional Grammar, Categorial Grammar, Construction Grammar, Dependency Grammar, and Minimalism)