Characterizing structural relationships in scenes using graph kernels

Quelles relations entretiennent les mouvements sociaux de 1968 et les mouvements féministes en Europe et en Amérique du Nord ? Telle est la question posée dans cet essai par Brigitte Studer, professeure d’histoire suisse et d’histoire moderne à l’Université de Berne. Cependant, ce ne sont pas tant les aspects théoriques – bien qu’il soit difficile d’en faire l’économie – qui sont au cœur de son propos mais bien la constitution d’une puissance agissante qui est au centre du questionnement de l..

Characterizing structural relationships in scenes using graph kernels

Modeling virtual environments is a time consuming and expensive task that is becoming increasingly popular for both professional and casual artists. The model density and complexity of the scenes rep-resenting these virtual environments is rising rapidly. This trend suggests that data-mining a 3D scene corpus to facilitate collabora-tive content creation could be a very powerful tool enabling more efficient scene design. In this paper, we show how to represent scenes as graphs that encode models and their semantic relation-ships. We then define a kernel between these relationship graphs that compares common virtual substructures in two graphs and cap-tures the similarity between their corresponding scenes. We apply this framework to several scene modeling problems, such as find-ing similar scenes, relevance feedback, and context-based model search. We show that incorporating structural relationships allows our method to provide a more relevant set of results when compared against previous approaches to model context search

iMAPPER: Interaction-guided Scene Mapping from Monocular Videos

Next generation smart and augmented reality systems demand a computational understanding of monocular footage that captures humans in physical spaces to reveal plausible object arrangements and human-object interactions. Despite recent advances, both in scene layout and human motion analysis, the above setting remains challenging to analyze due to regular occlusions that occur between objects and human motions. We observe that the interaction between object arrangements and human actions is often strongly correlated, and hence can be used to help recover from these occlusions. We present iMapper, a data-driven method to identify such human-object interactions and utilize them to infer layouts of occluded objects. Starting from a monocular video with detected 2D human joint positions that are potentially noisy and occluded, we first introduce the notion of interaction-saliency as space-time snapshots where informative human-object interactions happen. Then, we propose a global optimization to retrieve and fit interactions from a database to the detected salient interactions in order to best explain the input video. We extensively evaluate the approach, both quantitatively against manually annotated ground truth and through a user study, and demonstrate that iMapper produces plausible scene layouts for scenes with medium to heavy occlusion. Code and data are available on the project page

Edit propagation using geometric relationship functions

We propose a method for propagating edit operations in 2D vector graphics, based on geometric relationship functions. These functions quantify the geometric relationship of a point to a polygon, such as the distance to the boundary or the direction to the closest corner vertex. The level sets of the relationship functions describe points with the same relationship to a polygon. For a given query point, we first determine a set of relationships to local features, construct all level sets for these relationships, and accumulate them. The maxima of the resulting distribution are points with similar geometric relationships. We show extensions to handle mirror symmetries, and discuss the use of relationship functions as local coordinate systems. Our method can be applied, for example, to interactive floorplan editing, and it is especially useful for large layouts, where individual edits would be cumbersome. We demonstrate populating 2D layouts with tens to hundreds of objects by propagating relatively few edit operations