One of the grand challenges of artificial intelligence is to enable computers to interpret 3D
scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene
and object representation and inference from still images with a focus on recent efforts to
fuse models of geometry and perspective with statistical machine learning. The book is
organized into three sections: (1) Interpretation of Physical Space (2) Recognition of 3D
Objects and (3) Integrated 3D Scene Interpretation. The first discusses representations of
spatial layout and techniques to interpret physical scenes from images. The second section
introduces representations for 3D object categories that account for the intrinsically 3D
nature of objects and provide robustness to change in viewpoints. The third section discusses
strategies to unite inference of scene geometry and object pose and identity into a coherent
scene interpretation. Each section broadly surveys important ideas from cognitive science and
artificial intelligence research organizes and discusses key concepts and techniques from
recent work in computer vision and describes a few sample approaches in detail. Newcomers to
computer vision will benefit from introductions to basic concepts such as single-view geometry
and image classification while experts and novices alike may find inspiration from the book's
organization and discussion of the most recent ideas in 3D scene understanding and 3D object
recognition. Specific topics include: mathematics of perspective geometry visual elements of
the physical scene structural 3D scene representations techniques and features for image and
region categorization historical perspective computational models and datasets and machine
learning techniques for 3D object recognition inferences of geometrical attributes of objects
such as size and pose and probabilistic and feature-passing approaches for contextual
reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models
Single-view Geometry Modeling the Physical Scene Categorizing Images and Regions Examples
of 3D Scene Interpretation Background on 3D Recognition Modeling 3D Objects Recognizing
and Understanding 3D Objects Examples of 2D 1 2 Layout Models Reasoning about Objects and
Scenes Cascades of Classifiers Conclusion and Future Directions
