A review of vision-based gait recognition methods for human identification

Human identification by gait has created a great deal of interest in computer vision community due to its advantage of inconspicuous recognition at a relatively far distance. This paper provides a comprehensive survey of recent developments on gait recognition approaches. The survey emphasizes on three major issues involved in a general gait recognition system, namely gait image representation, feature dimensionality reduction and gait classification. Also, a review of the available public gait datasets is presented. The concluding discussions outline a number of research challenges and provide promising future directions for the field.

Managing depression in patients with vision impairment : a descriptive study of practitioners' beliefs and confidence

Aim: Depression is common in older adults with vision impairment yet it often remains unidentified and untreated.
Eye health professionals (EHPs) and rehabilitation workers (RWs) may be able to assist in detecting depression. This study identified EHPs’ and RWs’ beliefs about depression and confidence in working with patients with vision
impairment and depression.
Methods: A self-administered cross-sectional survey of 94 EHPs and RWs assessed beliefs about the symptoms and treatment for depression, and confidence in working with depressed people with vision impairment.
Results: Participants showed awareness of both the symptoms and treatment options for depression. However,
some important misconceptions were identified and many symptoms of depression were commonly attributed to
vision loss. Participants lacked confidence in communicating about depression with patients and their families.
Conclusions: Training programs are needed to enable EHPs and RWs to confidently identify depression and
discuss appropriate treatment and referral options with their patients.

A robust solution to the stereo-vision-based simultaneous localization and mapping problem with steady and moving landmarks

The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using recently developed ideas and algorithms from modern robust control and estimation theory. A nonlinear model for a stereo-vision-based sensor is derived that leads to nonlinear measurements of the landmark coordinates along with optical flow-based measurements of the relative robot-landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear domain and solved using a robust linear filter. Actually, the linear filter is guaranteed stable and the SLAM state estimation error is bounded within an ellipsoidal set. A mathematically rigorous stability proof is given that holds true even when the landmarks move in accordance with an unknown control input. No similar results are available for the commonly employed extended Kalman filter, which is known to exhibit divergence and inconsistency characteristics in practice. A number of illustrative examples are given using both simulated and real vision data that further validate the proposed method.

Doubling and convergence : novel models of vision and sense of space

Re-photography is considered in this paper as a synthesis of the processes of seeing, to develop an aesthetic of space.

This practice deals with being (noun and verb) in space and the perception of space and depiction of space; space at the intersection of landscape and human. A key to the conundrum of the figure and the ground arises out of practical photographic investigations to convey the very human sensations of being on the ground, in the confounding landscape of the Central Victorian (Australian) ironbark forests and goldfields.

What is revealed is that what we see, what we attend to, actually appears concentrated at the nodes of a series of vortices. Each vortex is a moiré interference of converging views of the same scene. Attention is a convergence on particulars. Like a magnetic field, the vortex remains invisible in our everyday vision, but it appears in these images. It is imprinted from individual perspectives at particular places; a new perspective with a point of apparition rather than of vanishing.

The impression that I get : educational inclusion explored through the voices of young people with vision impairment

Despite the notion of educational inclusion of students with disabilities increasing in popularity, the day-to-day reality of its effectiveness remains mostly unknown. This paper reports key findings of a small-scale qualitative study that was conducted with a group of young people with vision impairment who attended an inclusive secondary school. The aim of the research was to ascertain their voiced experiences of their inclusion. Relevant to the study was the researcher’s insider status, which allowed for his unique insight and shared experiences with participants to influence data collection and analysis. The students reported a constant trade off that occurred between their aspirations for access and autonomy and practices of other stakeholders in the school that both facilitated and inhibited their inclusion. In sum, the students’ inclusion was ineffective because of habitual inhibiting actions of others. Recommendations are made based on Slee’s (2001) call for altered teaching and learning realities to promote educational inclusion, and a model of social justice that could bring about increased student agency (Higgins, Macarthur & Kelly, 2009).

Optimal fault-tolerant robotic manipulators

This thesis addresses “Optimal Fault-Tolerant Robotic Manipulators” for locked-joint failures and consists of three components. It begins by investigating the regions of workspace where the manipulator can operate with high reliability. It then continues with an efficient deployment of kinematic redundancies for fault-tolerant operation. Finally, it presents a novel method for design of optimal fault-tolerant manipulators.

Stereo vision and wavelets/multiwavelets analysis : 3d reconstruction using wavelets/multiwavelets theory and stereo vision

During the image formation process of the camera, explicit 3D information about the scene or objects in the scene are lost. Therefore, 3D structure or depth information has to be inferred implicitly from the 2D intensity images. This problem is com- monly referred to as 3D reconstruction. In this work a complete 3D reconstruction algorithm is presented, capable of reconstructing dimensionally accurate 3D models of the objects, based on stereo vision and multi-resolution analysis. The developed system uses a reference depth model of the objects under observation to improve the disparity maps, estimated. Only a few features are extracted from that reference model, which are the relative location of the discontinuities and the z-dimensional extremes of objects depth. The maximum error deviation of the estimated depth along the surfaces is less than 0.5mm and along the discontinuities is less than 1.5mm. The developed system is invariant to illuminative variations, and orientation, location and scaling of the objects under consideration, which makes the developed system highly robust.

How honeybees make grazing landings on flat surfaces

Freely flying bees were filmed as they landed on a flat, horizontal surface, to investigate the underlying visuomotor control strategies. The results reveal that (1) landing bees approach the surface at a relatively shallow descent angle; (2) they tend to hold the angular velocity of the image of the surface constant as they approach it; and (3) the instantaneous speed of descent is proportional to the instantaneous forward speed. These characteristics reflect a surprisingly simple and effective strategy for achieving a smooth landing, by which the forward and descent speeds are automatically reduced as the surface is approached and are both close to zero at touchdown. No explicit knowledge of flight speed or height above the ground is necessary. A model of the control scheme is developed and its predictions are verified. It is also shown that, during landing, the bee decelerates continuously and in such a way as to keep the projected time to touchdown constant as the surface is approached. The feasibility of this landing strategy is demonstrated by implementation in a robotic gantry equipped with vision.

Hypothesis verification using parametric models and active vision strategies

This paper proposes a methodology for determining the shape and ultimately the functionality of objects from intensity images; 2D analytic functions are used to track 3D features during known camera motions. Three analytic functions are proposed that describe the relationship between pairs of points that are either stationary or moving depending on whether the points are on occluding boundaries or otherwise. Many of the problems of correspondence are reduced by using foveation, known camera motion, and active vision methods. The three analytic functions are shown to enable hypothesis refinement of the functionality of a number of 3D objects without full 3D information about the shape.

Insect-inspired robotic homing

Many animals, including insects, successfully engage in visual homing. We describe a system that allows a mobile robot to home. Specifically, we propose a simple, yet robust, homing scheme that only relies upon the observation of the bearings of visible landmarks. However, this can easily be extended to include other visual cues. The homing algorithm allows a mobile robot to home incrementally by moving in such a way as to gradually reduce the discrepancy between the current view and the view obtained from the home position. Both simulation and mobile robot experiments are used to demonstrate the feasibility of the approach.

Obtaining functional parametric models using active vision strategies

This paper addresses the problem of determining which 3D shape is present, and more importantly, the dimensions of the shape in a scene. This is performed in an active vision system because it reduces the complexity of the problem through the use of gaze stabilization, choice of foveation point, and selective processing by adaptively processing regions of interest. In our case, only a small number of equations and parameters are needed for each shape and these are incorporated into functional descriptions of the shapes.

Emerging hypothesis verification using function-based geometric models and active vision strategies

This paper describes an investigation into the use of parametric 2D models describing the movement of edges for the determination of possible 3D shape and hence function of an object. An assumption of this research is that the camera can foveate and track particular features. It is argued that simple 2D analytic descriptions of the movement of edges can infer 3D shape while the camera is moved. This uses an advantage of foveation i.e. the problem becomes object centred. The problem of correspondence for numerous edge points is overcome by the use of a tree based representation for the competing hypotheses. Numerous hypothesis are maintained simultaneously and it does not rely on a single kinematic model which assumes constant velocity or acceleration. The numerous advantages of this strategy are described.