Vision under mesopic and scotopic illumination

Evidence has accumulated that rod activation under mesopic and scotopic light levels alters visual perception and performance. Here we review the most recent developments in the measurement of rod and cone contributions to mesopic color perception and temporal processing, with a focus on data measured using the four-primary photostimulator method that independently controls rod and cone excitations. We discuss the findings in the context of rod inputs to the three primary retinogeniculate pathways to understand rod contributions to mesopic vision. Additionally, we present evidence that hue perception is possible under scotopic, pure rod-mediated conditions that involves cortical mechanisms.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Stationary processes for object detection and non-rigid structure-from-motion

Stationary processes are random variables whose value is a signal and whose distribution is invariant to translation in the domain of the signal. They are intimately connected to convolution, and therefore to the Fourier transform, since the covariance matrix of a stationary process is a Toeplitz matrix, and Toeplitz matrices are the expression of convolution as a linear operator. This thesis utilises this connection in the study of i) efficient training algorithms for object detection and ii) trajectory-based non-rigid structure-from-motion.

Extending visual perception with haptic exploration for improved scene understanding

Scene understanding has been investigated from a mainly visual information point of view. Recently depth has been provided an extra wealth of information, allowing more geometric knowledge to fuse into scene understanding. Yet to form a holistic view, especially in robotic applications, one can create even more data by interacting with the world. In fact humans, when growing up, seem to heavily investigate the world around them by haptic exploration. We show an application of haptic exploration on a humanoid robot in cooperation with a learning method for object segmentation. The actions performed consecutively improve the segmentation of objects in the scene.

The Perception of Light: Understanding Architectural Lighting Design

Light is essential to life and vision; without light, nothing exists. It plays a pivotal role in the world of architectural design and is used to generate all manner of perceptions that enhance the designed environment experience. But what are the fundamental elements that designers rely upon to generate light enhanced experiences? How are people’s perceptions influenced by designed light schemas? In this book Dr. Marisha McAuliffe highlights the relationship that exists between light source and surface and how both create quality of effect in the built environment. Concepts relating to architectural lighting design history, theories, research, and generation of lighting design schemes to create optimal experiences in architecture, interior architecture and design are all explored in detail. This book is essential reading for both the student and the professional working in architectural lighting, particularly in terms of qualitative perception oriented lighting design

Signal compression through spatial frequency-based motion estimation

The interest in low bit rate video coding has increased considerably. Despite rapid progress in storage density and digital communication system performance, demand for data-transmission bandwidth and storage capacity continue to exceed the capabilities of available technologies. The growth of data-intensive digital audio, video applications and the increased use of bandwidth-limited media such as video conferencing and full motion video have not only sustained the need for efficient ways to encode analog signals, but made signal compression central to digital communication and data-storage technology. In this paper we explore techniques for compression of image sequences in a manner that optimizes the results for the human receiver. We propose a new motion estimator using two novel block match algorithms which are based on human perception. Simulations with image sequences have shown an improved bit rate while maintaining ''image quality'' when compared to conventional motion estimation techniques using the MAD block match criteria.

Role of feedback in mammalian vision: a new hypothesis and a computational model

This paper presents a novel hypothesis on the function of massive feedback pathways in mammalian visual systems. We propose that the cortical feature detectors compete not for the right to represent the output at a point, but for exclusive rights to abstract and represent part of the underlying input. Feedback can do this very naturally. A computational model that implements the above idea for the problem of line detection is presented and based on that we suggest a functional role for the thalamo-cortical loop during perception of lines. We show that the model successfully tackles the so called Cross problem. Based on some recent experimental results, we discuss the biological plausibility of our model. We also comment on the relevance of our hypothesis (on the role of feedback) to general sensory information processing and recognition. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

Object Tracking Using Motion Direction Detection

We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.

Constrained 3D sketching with haptics and active motion annotation

The aim of this work is to enable seamless transformation of product concepts to CAD models. This necessitates availability of 3D product sketches. The present work concerns intuitive generation of 3D strokes and intrinsic support for space sharing and articulation for the components of the product being sketched. Direct creation of 3D strokes in air lacks in precision, stability and control. The inadequacy of proprioceptive feedback for the task is complimented in this work with stereo vision and haptics. Three novel methods based on pencil-paper interaction analogy for haptic rendering of strokes have been investigated. The pen-tilt based rendering is simpler and found to be more effective. For the spatial conformity, two modes of constraints for the stylus movements, corresponding to the motions on a control surface and in a control volume have been studied using novel reactive and field based haptic rendering schemes. The field based haptics, which in effect creates an attractive force field near a surface, though non-realistic, provided highly effective support for the control-surface constraints. The efficacy of the reactive haptic rendering scheme for the constrained environments has been demonstrated using scribble strokes. This can enable distributed collaborative 3D concept development. The notion of motion constraints, defined through sketch strokes enables intuitive generation of articulated 3D sketches and direct exploration of motion annotations found in most product concepts. The work, thus, establishes that modeling of the constraints is a central issue in 3D sketching.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.

Assessment of driver vision functions in relation to their crash involvement in India

Among the human factors that influence safe driving, visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the effect of visual functions of drivers in India on their road crash involvement. Experiments were conducted to assess vision functions of Indian licensed drivers belonging to various organizations, age groups and driving experience. The test results were further related to the crash involvement histories of drivers through statistical tools. A generalized linear model was developed to ascertain the influence of these traits on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision, depth perception, contrast sensitivity, acuity and phoria were found to influence their crash involvement rates. In India, there are no efficient standards and testing methods to assess the visual capabilities of drivers during their licensing process and this study highlights the need for the same.