1,721,064 research outputs found
Special Issue on Omnidirectional Robot Vision
No full textSpecial Issue on Omnidirectional Robot Visio
2nd. Workshop on Omnidirectional Robot Vision
No full textProceedings of the 2nd. Workshop on Omnidirectional Robot Vision A workshop of the 2010 IEEE International Conference on Robotics and Automation (ICRA2010) Anchorage, Alaska, USA, May 7, 2010
Revisiting Viewing Graph Solvability: an Effective Approach Based on Cycle Consistency
Full text linkIn the structure from motion, the viewing graph is a graph where the vertices correspond to cameras (or images) and the edges represent the fundamental matrices. We provide a new formulation and an algorithm for determining whether a viewing graph is solvable, i.e., uniquely determines a set of projective cameras. The known theoretical conditions either do not fully characterize the solvability of all viewing graphs, or are extremely difficult to compute because they involve solving a system of polynomial equations with a large number of unknowns. The main result of this paper is a method to reduce the number of unknowns by exploiting cycle consistency. We advance the understanding of solvability by (i) finishing the classification of all minimal graphs up to 9 nodes, (ii) extending the practical verification of solvability to minimal graphs with up to 90 nodes, (iii) finally answering an open research question by showing that finite solvability is not equivalent to solvability, and (iv) formally drawing the connection with the calibrated case (i.e., parallel rigidity). Finally, we present an experiment on real data that shows that unsolvable graphs may appear in practice
Viewing Graph Solvability via Cycle Consistency
No full textIn structure-from-motion the viewing graph is a graph where vertices correspond to cameras and edges represent fundamental matrices. We provide a new formulation and an algorithm for establishing whether a viewing graph is solvable, i.e. it uniquely determines a set of projective cameras. Known theoretical conditions either do not fully characterize the solvability of all viewing graphs, or are exceedingly hard to compute for they involve solving a system of polynomial equations with a large number of unknowns. The main result of this paper is a method for reducing the number of unknowns by exploiting the cycle consistency. We advance the understanding of the solvability by (i) finishing the classification of all previously undecided minimal graphs up to 9 nodes, (ii) extending the practical solvability testing up to minimal graphs with up to 90 nodes, and (iii) definitely answering an open research question by showing that the finite solvability is not equivalent to the solvability. Finally, we present an experiment on real data showing that unsolvable graphs are appearing in practical situations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Guest Editorial: Special Issue on Traditional Computer Vision in the Age of Deep Learning
No full textA Direct Approach to Viewing Graph Solvability
No full textThe viewing graph is a useful way to represent uncalibrated cameras and their geometric relationships: nodes correspond to cameras and edges represent fundamental matrices. By analyzing this graph, it is possible to establish if the problem is “solvable” in the sense that there exists a unique (up to a single projective transformation) set of cameras that are compliant with the given fundamental matrices. In this paper, we take several steps forward in the study of viewing graph solvability: we propose a new formulation of the problem that is more direct than previous literature, based on a formula that explicitly links pairs of cameras via their fundamental matrix; we introduce the new concept of “infinitesimal solvability”, demonstrating its usefulness in understanding real structure from motion graphs; we propose an algorithm for testing infinitesimal solvability and extracting components of unsolvable cases, that is more efficient than previous work; we set up an open question on the connection between infinitesimal solvability and solvability
Viewing Graph Solvability in Practice
Full text linkWe present an advance in understanding the projective Structure-from-Motion, focusing in particular on the viewing graph: such a graph has cameras as nodes and fundamental matrices as edges. We propose a practical method for testing finite solvability, i.e., whether a viewing graph induces a finite number of camera configurations. Our formulation uses a significantly smaller number of equations (up to 400×) with respect to previous work. As a result, this is the only method in the literature that can be applied to large viewing graphs coming from real datasets, comprising up to 300K edges. In addition, we develop the first algorithm for identifying maximal finite-solvable components
- …
