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arXiv · 1807.05933

Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoning

Paul Gay·Stuart James·Alessio Del Bue
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Abstract

Recent approaches on visual scene understanding attempt to build a scene graph -- a computational representation of objects and their pairwise relationships. Such rich semantic representation is very appealing, yet difficult to obtain from a single image, especially when considering complex spatial arrangements in the scene. Differently, an image sequence conveys useful information using the multi-view geometric relations arising from camera motion. Indeed, in such cases, object relationships are naturally related to the 3D scene structure. To this end, this paper proposes a system that first computes the geometrical location of objects in a generic scene and then efficiently constructs scene graphs from video by embedding such geometrical reasoning. Such compelling representation is obtained using a new model where geometric and visual features are merged using an RNN framework. We report results on a dataset we created for the task of 3D scene graph generation in multiple views.

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Paul Gay, Stuart James, Alessio Del Bue. 2018-07-16. Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoning. https://arxiv.org/abs/1807.05933

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