Abstract
With the availability of low-cost and compact 2.5/3D visual sensing devices,
computer vision community is experiencing a growing interest in visual scene
understanding. This survey paper provides a comprehensive background to this
research topic. We begin with a historical perspective, followed by popular 3D
data representations and a comparative analysis of available datasets. Before
delving into the application specific details, this survey provides a succinct
introduction to the core technologies that are the underlying methods
extensively used in the literature. Afterwards, we review the developed
techniques according to a taxonomy based on the scene understanding tasks. This
covers holistic indoor scene understanding as well as subtasks such as scene
classification, object detection, pose estimation, semantic segmentation, 3D
reconstruction, saliency detection, physics-based reasoning and affordance
prediction. Later on, we summarize the performance metrics used for evaluation
in different tasks and a quantitative comparison among the recent
state-of-the-art techniques. We conclude this review with the current
challenges and an outlook towards the open research problems requiring further
investigation.
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