<title>Automatically planning the inspection of three-dimensional objects using stereo computer vision</title>

Visual representation of three-dimensional (3-D) objects in our environment is a crucial question, for human as well as for machine vision. Some basics are reviewed of a viewer-centred model of 3-D objects, aspect graphs, which represents a 3-D object by all its topologically stable visible image contours (its aspects) and by the transitions between stable image contours (the visual events). This representation takes only geometrical information about discontinuities in depth and in surface orientation into account, and other clues, such as shadows, markings, texture, etc, are disregarded. Mathematical results give some insight into the relationships between the geometry of a 3-D object and the aspect of its image contours, the techniques used to compute an aspect graph effectively, and the state of the art of this type of model in computer vision. Current research is reviewed on viewer-centred representation in cognitive science that seems to indicate that aspect graphs could also have some relevance for human vision.

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Analytical Modeling for Three Dimensional Objects Using Computer Vision.(Dept.E)

MEJ. Mansoura Engineering Journal ◽

10.21608/bfemu.2021.189401 ◽

2021 ◽

Vol 13 (1) ◽

pp. 91-98

Author(s):

Yehia Enab ◽

Fayez Zaki ◽

A. Abd El-Fattah ◽

S. El-Konyaly

Keyword(s):

Computer Vision ◽

Analytical Modeling ◽

Three Dimensional ◽

Three Dimensional Objects

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Three-Dimensional Computer Vision

10.1007/978-3-642-82429-6 ◽

1987 ◽

Cited By ~ 146

Author(s):

Yoshiaki Shirai

Keyword(s):

Computer Vision ◽

Three Dimensional

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Fast Overlap Detection between Hard-Core Colloidal Cuboids and Spheres. The OCSI Algorithm

Algorithms ◽

10.3390/a14030072 ◽

2021 ◽

Vol 14 (3) ◽

pp. 72

Author(s):

Luca Tonti ◽

Alessandro Patti

Keyword(s):

Colloidal Particles ◽

Dynamic Properties ◽

Wide Spectrum ◽

Three Dimensional ◽

Hard Core ◽

Detection Algorithm ◽

Three Dimensional Objects ◽

Aggregation Behaviour ◽

Sphere Radius ◽

User Friendly

Collision between rigid three-dimensional objects is a very common modelling problem in a wide spectrum of scientific disciplines, including Computer Science and Physics. It spans from realistic animation of polyhedral shapes for computer vision to the description of thermodynamic and dynamic properties in simple and complex fluids. For instance, colloidal particles of especially exotic shapes are commonly modelled as hard-core objects, whose collision test is key to correctly determine their phase and aggregation behaviour. In this work, we propose the Oriented Cuboid Sphere Intersection (OCSI) algorithm to detect collisions between prolate or oblate cuboids and spheres. We investigate OCSI’s performance by bench-marking it against a number of algorithms commonly employed in computer graphics and colloidal science: Quick Rejection First (QRI), Quick Rejection Intertwined (QRF) and a vectorized version of the OBB-sphere collision detection algorithm that explicitly uses SIMD Streaming Extension (SSE) intrinsics, here referred to as SSE-intr. We observed that QRI and QRF significantly depend on the specific cuboid anisotropy and sphere radius, while SSE-intr and OCSI maintain their speed independently of the objects’ geometry. While OCSI and SSE-intr, both based on SIMD parallelization, show excellent and very similar performance, the former provides a more accessible coding and user-friendly implementation as it exploits OpenMP directives for automatic vectorization.

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Proposing 3D Thermal Technology for Heritage Building Energy Monitoring

Remote Sensing ◽

10.3390/rs13081537 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1537

Author(s):

Antonio Adán ◽

Víctor Pérez ◽

José-Luis Vivancos ◽

Carolina Aparicio-Fernández ◽

Samuel A. Prieto

Keyword(s):

Computer Vision ◽

Dimensional Space ◽

Three Dimensional ◽

Building Energy ◽

Energy Monitoring ◽

3D Computer Vision ◽

Building Monitoring ◽

Heritage Buildings ◽

Heritage Building ◽

Definition Of

The energy monitoring of heritage buildings has, to date, been governed by methodologies and standards that have been defined in terms of sensors that record scalar magnitudes and that are placed in specific positions in the scene, thus recording only some of the values sampled in that space. In this paper, however, we present an alternative to the aforementioned technologies in the form of new sensors based on 3D computer vision that are able to record dense thermal information in a three-dimensional space. These thermal computer vision-based technologies (3D-TCV) entail a revision and updating of the current building energy monitoring methodologies. This paper provides a detailed definition of the most significant aspects of this new extended methodology and presents a case study showing the potential of 3D-TCV techniques and how they may complement current techniques. The results obtained lead us to believe that 3D computer vision can provide the field of building monitoring with a decisive boost, particularly in the case of heritage buildings.

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ALPACA: a fast and accurate computer vision approach for automated landmarking of three‐dimensional biological structures

Methods in Ecology and Evolution ◽

10.1111/2041-210x.13689 ◽

2021 ◽

Author(s):

Arthur Porto ◽

Sara Rolfe ◽

A. Murat Maga

Keyword(s):

Computer Vision ◽

Three Dimensional ◽

Biological Structures

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The Effect of Material Properties on the Perceived Shape of Three-Dimensional Objects

i-Perception ◽

10.1177/2041669520982317 ◽

2020 ◽

Vol 11 (6) ◽

pp. 204166952098231

Author(s):

Masakazu Ohara ◽

Juno Kim ◽

Kowa Koida

Keyword(s):

Material Properties ◽

Regional Variation ◽

Three Dimensional ◽

Mean Square ◽

Viewing Condition ◽

Three Dimensional Objects ◽

Transparent Objects ◽

Dimensional Shape ◽

Local Root ◽

Three Dimensional Shape

Perceiving the shape of three-dimensional objects is essential for interacting with them in daily life. If objects are constructed from different materials, can the human visual system accurately estimate their three-dimensional shape? We varied the thickness, motion, opacity, and specularity of globally convex objects rendered in a photorealistic environment. These objects were presented under either dynamic or static viewing condition. Observers rated the overall convexity of these objects along the depth axis. Our results show that observers perceived solid transparent objects as flatter than the same objects rendered with opaque reflectance properties. Regional variation in local root-mean-square image contrast was shown to provide information that is predictive of perceived surface convexity.

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