NDLI: Emerging images

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Layered shape synthesis: automatic generation of control maps for non-stationary textures

Interactive design of urban spaces using geometrical and behavioral modeling

Patch-based image vectorization with automatic curvilinear feature alignment

Harmonic shells: a practical nonlinear sound model for near-rigid thin shells

Sketch2Photo: internet image montage

Printing spatially-varying reflectance

Micro-rendering for scalable, parallel final gathering

Relief analysis and extraction

Adaptive wavelet rendering

Removing image artifacts due to dirty camera lenses and thin occluders

Structured annotations for 2D-to-3D modeling

Ray casting of multiple volumetric datasets with polyhedral boundaries on manycore GPUs

Evaluation of reverse tone mapping through varying exposure conditions

Capturing hair assemblies fiber by fiber

Optimizing walking controllers

Out-of-core multigrid solver for streaming meshes

Feature-aligned shape texturing

Procedural modeling of structurally-sound masonry buildings

A GPU Laplacian solver for diffusion curves and Poisson image editing

Stretching and wiggling liquids

Optimized image resizing using seam carving and scaling

Interactive reflection editing

All-frequency rendering of dynamic, spatially-varying reflectance

Abstraction of man-made shapes

Stochastic progressive photon mapping

Fast motion deblurring

Analytic drawing of 3D scaffolds

Debugging GPU stream programs through automatic dataflow recording and visualization

3D polyomino puzzle

Robust color-to-gray via nonlinear global mapping

A practical approach for photometric acquisition of hair color

Compact character controllers

Dynamic shape capture using multi-view photometric stereo

Continuity mapping for multi-chart textures

Symmetric architecture modeling with a single image

Rendering surface details with diffusion curves

Synthetic turbulence using artificial boundary layers

A system for retargeting of streaming video

User-assisted intrinsic images

Depth-of-field rendering with multiview synthesis

Partial intrinsic reflectional symmetry of 3D shapes

Automatic bounding of programmable shaders for efficient global illumination

Noise brush: interactive high quality image-noise separation

DiagSplit: parallel, crack-free, adaptive tessellation for micropolygon rendering

Real-time parallel hashing on the GPU

The graph camera

Structure-aware error diffusion

Robust task-based control policies for physics-based characters

Robust single-view geometry and motion reconstruction

Motion field texture synthesis

Image-based street-side city modeling

Efficient affinity-based edit propagation using K-D tree

Aggregate dynamics for dense crowd simulation

Motion-aware temporal coherence for video resizing

Webcam clip art: appearance and illuminant transfer from time-lapse sequences

Amortized supersampling

Packing circles and spheres on surfaces

Virtual spherical lights for many-light rendering of glossy scenes

Edge-preserving multiscale image decomposition based on local extrema

Approximating subdivision surfaces with Gregory patches for hardware tessellation

RenderAnts: interactive Reyes rendering on GPUs

BiDi screen: a thin, depth-sensing LCD for 3D interaction using light fields

Emerging images

Exploratory modeling with collaborative design spaces

Modeling spatial and temporal variation in motion data

Consolidation of unorganized point clouds for surface reconstruction

Skipping steps in deformable simulation with online model reduction

Real-time prosody-driven synthesis of body language

Emerging images

Content Provider	ACM Digital Library
Author	Yeshurun, Hezy Chu, Hung-Kuo Mitra, Niloy J. Cohen-Or, Daniel Wolf, Lior Lee, Tong-Yee
Abstract	Emergence refers to the unique human ability to aggregate information from seemingly meaningless pieces, and to perceive a whole that is meaningful. This special skill of humans can constitute an effective scheme to tell humans and machines apart. This paper presents a synthesis technique to generate images of 3D objects that are detectable by humans, but difficult for an automatic algorithm to recognize. The technique allows generating an infinite number of images with emerging figures. Our algorithm is designed so that locally the synthesized images divulge little useful information or cues to assist any segmentation or recognition procedure. Therefore, as we demonstrate, computer vision algorithms are incapable of effectively processing such images. However, when a human observer is presented with an emergence image, synthesized using an object she is familiar with, the figure emerges when observed as a whole. We can control the difficulty level of perceiving the emergence effect through a limited set of parameters. A procedure that synthesizes emergence images can be an effective tool for exploring and understanding the factors affecting computer vision techniques.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781605588582
DOI	10.1145/1661412.1618509
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-12-17
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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