RecceMan: an interactive recognition assistance for image-based reconnaissance: synergistic effects of human perception and computational methods for object recognition, identification, and infrastructure analysis

2015 ◽  
Author(s):  
Nadia El Bekri ◽  
Susanne Angele ◽  
Martin Ruckhäberle ◽  
Elisabeth Peinsipp-Byma ◽  
Bruno Haelke
Keyword(s):  
Object Recognition ◽  
Computational Methods ◽  
Synergistic Effects ◽  
Human Perception

scholarly journals Dynamic Color Object Recognition Using Fuzzy Logic

2004 ◽  
Vol 8 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Napoleon H. Reyes ◽  
◽  
Elmer P. Dadios ◽  
Keyword(s):  
Object Recognition ◽  
Fuzzy Inference ◽  
Color Constancy ◽  
Human Perception ◽  
Light Sources ◽  
Inference System ◽  
Image Appearance ◽  
Color Descriptors ◽  
New Perspective ◽  
Color Object Recognition

This paper presents a novel Logit-Logistic Fuzzy Color Constancy (LLFCC) algorithm and its variants for dynamic color object recognition. Contrary to existing color constancy algorithms, the proposed scheme focuses on manipulating a color locus depicting the colors of an object, and not stabilizing the whole image appearance per se. In this paper, a new set of adaptive contrast manipulation operators is introduced and utilized in conjunction with a fuzzy inference system. Moreover, a new perspective in extracting color descriptors of an object from the rg-chromaticity space is presented. Such color descriptors allow for the reduction of the effects of brightness/darkness and at the same time adhere to human perception of colors. The proposed scheme tremendously cuts processing time by simultaneously compensating for the effects of a multitude of factors that plague the scene of traversal, eliminating the need for image pre-processing steps. Experiment results attest to its robustness in scenes with multiple white light sources, spatially varying illumination intensities, varying object position, and presence of highlights.

Roman Cyborgs! On Significant Otherness, Material Absence, and Virtual Presence in the Archaeology of Roman Religion

2019 ◽  
Vol 23 (1) ◽  
pp. 64-81
Author(s):  
Eva Mol
Keyword(s):  
Computational Methods ◽  
Digital Technologies ◽  
Human Perception ◽  
Human Experience ◽  
Roman Religion ◽  
The Past ◽  
Digital World ◽  
Virtual Presence ◽  
Digital Archaeology ◽  
Expanded Concept

In this article I explore different ways archaeologists can contribute to and learn from theorizing the digital world beyond the traditional functionalistic means of applying computational methods. I argue that current digital technologies can be a very constructive tool to create non-human experience and awareness. I pursue this argument by presenting ideas from a work-in-progress project experimenting with the post-human and the virtual, and by exploring significant otherness in Roman religion and the dark spots in human perception, through the analysis of an absent temple in Rome. Applying post-human philosophies and an expanded concept of virtuality beyond the digital makes it possible to change our approach to object/human/divine relations in Roman cults and how we present Roman heritage towards a post-humanist framework. Through this, digital archaeology can become one of the ways of re-examining and reinventing our ideas of the human, the past and the digital.

scholarly journals Qualitative similarities and differences in visual object representations between brains and deep networks

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Georgin Jacob ◽  
R. T. Pramod ◽  
Harish Katti ◽  
S. P. Arun
Keyword(s):  
Neural Networks ◽  
Object Recognition ◽  
Deep Neural Networks ◽  
Relative Size ◽  
Sufficient Conditions ◽  
Human Perception ◽  
Visual Object ◽  
Object Representations ◽  
Deep Networks ◽  
Global Advantage

AbstractDeep neural networks have revolutionized computer vision, and their object representations across layers match coarsely with visual cortical areas in the brain. However, whether these representations exhibit qualitative patterns seen in human perception or brain representations remains unresolved. Here, we recast well-known perceptual and neural phenomena in terms of distance comparisons, and ask whether they are present in feedforward deep neural networks trained for object recognition. Some phenomena were present in randomly initialized networks, such as the global advantage effect, sparseness, and relative size. Many others were present after object recognition training, such as the Thatcher effect, mirror confusion, Weber’s law, relative size, multiple object normalization and correlated sparseness. Yet other phenomena were absent in trained networks, such as 3D shape processing, surface invariance, occlusion, natural parts and the global advantage. These findings indicate sufficient conditions for the emergence of these phenomena in brains and deep networks, and offer clues to the properties that could be incorporated to improve deep networks.

Analyzing color harmony of food images

2019 ◽  
Vol 2019 (1) ◽  
pp. 369-374
Author(s):  
Gianluigi Ciocca ◽  
Paolo Napoletano ◽  
Raimondo Schettini ◽  
Isabella Gagliardi ◽  
Maria Teresa Artese
Keyword(s):  
Computational Methods ◽  
Food Quality ◽  
Food Choice ◽  
Human Perception ◽  
Color Segmentation ◽  
Computational Pipeline ◽  
Color Palette ◽  
Color Harmony ◽  
Food Images

Color of food images play a key role in human perception of food quality and calories, as well as in food choice. In this paper we investigate the use of computational methods for color harmony analysis of food images. To this end we propose a computational pipeline that includes color segmentation, color palette extraction and color harmony prediction. Such a pipeline makes it possible to analyze the emotions elicited by pairs and multiple combinations of food dishes.

Proposal for ASCII coded phonetic script

1981 ◽  
Vol 11 (2) ◽  
pp. 62-74 ◽  
Author(s):  
J. B. Millar ◽  
H. Oasa
Keyword(s):  
Computational Methods ◽  
Digital Computer ◽  
Human Perception ◽  
Considerable Progress ◽  
Speech Communication ◽  
Analysis And Synthesis ◽  
Traditional Discipline ◽  
Made In

One of the challenges of current research into speech communication is that of effectively using the power of the digital computer to both organize data and to extract relevant relationships by computational methods. Whilst considerable progress has been made in the analysis and synthesis of the acoustics of speech and in understanding the perceptual mechanisms at work in human perception of speech, there has been a paucity of relations between such knowledge and the description of speech by the traditional discipline of phonetics. One significant factor in this situation is the lack of an effective way for the speech scientist to code the descriptions of the phonetician in a way that preserves the richness of description and accuracy of judgement attained by a highly trained ear and expressed in specialized phonetic scripts. It is the intent of this paper to propose a tool that could provide improved communication between the two disciplines.

Human Perception of Structure in Shaded Space-Filling Visualizations

2006 ◽  
Vol 5 (1) ◽  
pp. 47-61 ◽  
Author(s):  
Pourang Irani ◽  
Dean Slonowsky ◽  
Peer Shajahan
Keyword(s):  
Object Recognition ◽  
Negative Impact ◽  
Structural Information ◽  
Subjective Evaluation ◽  
Recognition Task ◽  
Human Perception ◽  
Visualization Tool ◽  
Structural Elements ◽  
Space Filling ◽  
Visualization Systems

Very early in the object recognition process the human visual system extracts shading information. While shading can enhance the visibility of structures, it can have a negative impact on the judgment of sizes of elements in a structure. In certain visualization systems the underlying hierarchical structure is not noticeably explicit, such as in space-filling techniques. We hypothesize that in such cases, shading can make the structure more explicit. In this paper, we report the results of two experiments designed to investigate the effects of shading information on extracting the structure in space-filling visualizations. In the first experiment subjects performed better with the visualization tool with shading on structure-based tasks. Our results do not show that shading impairs users' judgment on size-based tasks. A subjective evaluation shows that users preferred interacting with the system when shading was available. The second experiment was designed to investigate further users' capacity to identify structural elements within the space-filling visualization. A substructure recognition task was employed in this experiment and results show that users are capable of identifying sub-structures quicker and with fewer errors when the visualization tool was equipped with shading information than without. The results of both experiments provide evidence that shading information can be used to effectively obtain structural information from spacefilling visualizations.

Morphology of High-Performance Rigid-Rod Polymer Fibers and Molecular Composites

1989 ◽  
Vol 47 ◽  
pp. 338-339
Author(s):  
W.W. Adams ◽  
S. J. Krause
Keyword(s):  
Tensile Strength ◽  
High Performance ◽  
Liquid Crystalline ◽  
Molecular Level ◽  
Synergistic Effects ◽  
Tensile Modulus ◽  
Commercial Development ◽  
The Matrix ◽  
Molecular Composites ◽  
Rigid Rod

Rigid-rod polymers such as PBO, poly(paraphenylene benzobisoxazole), Figure 1a, are now in commercial development for use as high-performance fibers and for reinforcement at the molecular level in molecular composites. Spinning of liquid crystalline polyphosphoric acid solutions of PBO, followed by washing, drying, and tension heat treatment produces fibers which have the following properties: density of 1.59 g/cm3; tensile strength of 820 kpsi; tensile modulus of 52 Mpsi; compressive strength of 50 kpsi; they are electrically insulating; they do not absorb moisture; and they are insensitive to radiation, including ultraviolet. Since the chain modulus of PBO is estimated to be 730 GPa, the high stiffness also affords the opportunity to reinforce a flexible coil polymer at the molecular level, in analogy to a chopped fiber reinforced composite. The objectives of the molecular composite concept are to eliminate the thermal expansion coefficient mismatch between the fiber and the matrix, as occurs in conventional composites, to eliminate the interface between the fiber and the matrix, and, hopefully, to obtain synergistic effects from the exceptional stiffness of the rigid-rod molecule. These expectations have been confirmed in the case of blending rigid-rod PBZT, poly(paraphenylene benzobisthiazole), Figure 1b, with stiff-chain ABPBI, poly 2,5(6) benzimidazole, Fig. 1c A film with 30% PBZT/70% ABPBI had tensile strength 190 kpsi and tensile modulus of 13 Mpsi when solution spun from a 3% methane sulfonic acid solution into a film. The modulus, as predicted by rule of mixtures, for a film with this composition and with planar isotropic orientation, should be 16 Mpsi. The experimental value is 80% of the theoretical value indicating that the concept of a molecular composite is valid.

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