Human vision: Some objective explorations.

This chapter deals with two related problems occurring frequently in the physical sciences: first, the problem of estimating the value of a function from a limited number of data points; and second, the problem of calculating its value from a series approximation. Numerical methods for interpolating and extrapolating data are presented. The famous Lagrange interpolating polynomial is introduced and applied to one-dimensional and multidimensional problems. Cubic spline interpolation is introduced and an implementation in terms of Eigen classes is given. Several techniques for improving the convergence of Taylor series are discussed, including Shank’s transformation, Richardson extrapolation, and the use of Padé approximants. Conversion between representations with the quotient-difference algorithm is discussed. The exercises explore public transportation, human vision, the wine market, and SU(2) lattice gauge theory, among other topics.

Download Full-text

The Curious Eye

10.1093/oso/9780198850199.001.0001 ◽

2020 ◽

Author(s):

Erin Webster

Keyword(s):

Seventeenth Century ◽

Human Vision ◽

Francis Bacon ◽

Robert Hooke ◽

Robert Boyle ◽

Isaac Newton ◽

Johannes Kepler ◽

The Social ◽

The Subject ◽

Historical Moment

The Curious Eye explores early modern debates over two related questions: what are the limits of human vision, and to what extent can these limits be overcome by technological enhancement? Today, in our everyday lives we rely on optical technology to provide us with information about visually remote spaces even as we question the efficacy and ethics of such pursuits. But the debates surrounding the subject of technologically mediated vision have their roots in a much older literary tradition in which the ability to see beyond the limits of natural human vision is associated with philosophical and spiritual insight as well as social and political control. The Curious Eye provides insight into the subject of optically mediated vision by returning to the literature of the seventeenth century, the historical moment in which human visual capacity in the West was first extended through the application of optical technologies to the eye. Bringing imaginative literary works by Francis Bacon, John Milton, Margaret Cavendish, and Aphra Behn together with optical and philosophical treatises by Johannes Kepler, René Descartes, Robert Hooke, Robert Boyle, and Isaac Newton, The Curious Eye explores the social and intellectual impact of the new optical technologies of the seventeenth century on its literature. At the same time, it demonstrates that social, political, and literary concerns are not peripheral to the optical science of the period but rather an integral part of it, the legacy of which we continue to experience.

Download Full-text

Inhibition and disinhibition of direction-specific mechanisms in human vision

Nature ◽

10.1038/254692a0 ◽

1975 ◽

Vol 254 (5502) ◽

pp. 692-694 ◽

Cited By ~ 41

Author(s):

EUGENE LEVINSON ◽

ROBERT SEKULER

Keyword(s):

Human Vision

Download Full-text

A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189877 ◽

2021 ◽

pp. 1-11

Author(s):

Kusan Biswas

Keyword(s):

Data Hiding ◽

High Capacity ◽

Error Correcting Codes ◽

Human Vision ◽

Data Embedding ◽

Compressed Images ◽

Matrix Encoding ◽

Dct Coefficients ◽

Capacity Data ◽

Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

Download Full-text

Recognising the dynamic form of fire

Scientific Reports ◽

10.1038/s41598-021-89453-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Fintan Nagle ◽

Alan Johnston

Keyword(s):

Sequential Analysis ◽

Recognition Performance ◽

Human Vision ◽

Sequence Length ◽

False Alarms ◽

Analysis Model ◽

Sequence Recognition ◽

Asymmetric Pattern ◽

Dynamic Form ◽

Decision Making Model

AbstractEncoding and recognising complex natural sequences provides a challenge for human vision. We found that observers could recognise a previously presented segment of a video of a hearth fire when embedded in a longer sequence. Recognition performance declined when the test video was spatially inverted, but not when it was hue reversed or temporally reversed. Sampled motion degraded forwards/reversed playback discrimination, indicating observers were sensitive to the asymmetric pattern of motion of flames. For brief targets, performance increased with target length. More generally, performance depended on the relative lengths of the target and embedding sequence. Increased errors with embedded sequence length were driven by positive responses to non-target sequences (false alarms) rather than omissions. Taken together these observations favour interpreting performance in terms of an incremental decision-making model based on a sequential statistical analysis in which evidence accrues for one of two alternatives. We also suggest that prediction could provide a means of providing and evaluating evidence in a sequential analysis model.

Download Full-text