Change in colour appearance of small defocused lights

Small long wavelength lights (≤ 1’ arc) change colour appearance with positive defocus, appearing yellow or white. I investigated influences of longitudinal chromatic aberration and monochromatic aberrations on colour appearance of small narrow band lights. Seven cyclopleged participants viewed a small light (1’ arc diameter, λmax range 510 - 628 nm) centred within a 4.6’ black annulus and surrounded by a uniform white field under photopic light levels. An optical trombone varied focus. Participants were required to vary the focus by moving the optical trombone in either positive or negative direction and report when they noticed a change in appearance of the defocused narrow band light. Longitudinal chromatic aberration was controlled using a Powell achromatizing lens and its doublet and triplet components that neutralized, doubled and reversed the eye’s chromatic aberration, respectively. Changes in colour appearance for a 628 nm light occurred without any lens at +0.5 ± 0.2D defocus and with the doublet at +0.6 ± 0.2 D. The achromatizing lens did not affect appearance and the phenomenon was evident with the triplet for negative defocus (-0.5 ± 0.3 D). Adaptive optics correction of astigmatism and higher order monochromatic aberration did not affect magnitude significantly. Colour changes occurred despite a range of participant L/M cone ratios. Direction of change in colour appearance was reversed for short compared to long wavelengths. We conclude that longitudinal chromatic aberrations, but not monochromatic aberrations, are involved in changing appearance of small lights with defocus. Additional neuronal mechanisms that may contribute to the colour changes are considered.

Cascading appearance-based features for visual speaker verification

The cascading appearance-based (CAB) feature extraction technique has established itself as the state of the art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the speech recognition application also provide similar improvements for speaker recognition. These results suggest that visual speaker recognition can improve considerable when conducted solely through a consideration of the dynamic speech information rather than the static appearance of the speaker's mouth region.

Effect of optical aberrations on the colour appearance of small lights

Purpose: Small red lights (one minute of arc or less) change colour appearance with positive defocus. We investigated the influence of longitudinal chromatic aberration and monochromatic aberrations on the colour appearance of small narrow band lights. Methods: Seven cyclopleged, trichromatic observers viewed a small light (one minute of arc, λmax = 510, 532, 550, 589, 620, 628 nm, approximately 19 per cent Weber contrast) centred within a black annulus (4.5 minutes of arc) and surrounded by a uniform white field (2,170 cd/m2). Pupil size was four millimetres. An optical trombone varied focus. Longitudinal chromatic aberration was controlled with a two component Powell achromatising lens that neutralises the eye’s chromatic aberration; a doublet that doubles and a triplet that reverses the eye’s chromatic aberration. Astigmatism and higher order monochromatic aberrations were corrected using adaptive optics. Results: Observers reported a change in appearance of the small red light (628 nm) without the Powell lens at +0.49 ± 0.21 D defocus and with the doublet at +0.62 ± 0.16 D. Appearance did not alter with the Powell lens, and five of seven observers reported the phenomenon with the triplet for negative defocus (-0.80 ± 0.47 D). Correction of aberrations did not significantly affect the magnitude at which the appearance of the red light changed (+0.44 ± 0.18 D without correction; +0.46 ± 0.16 D with correction). The change in colour appearance with defocus extended to other wavelengths (λmax = 510 to 620 nm), with directions of effects being reversed for short wavelengths relative to long wavelengths. Conclusions: Longitudinal chromatic aberrations but not monochromatic aberrations are involved in changing the appearance of small lights with defocus.

FAB-MAP + RatSLAM : appearance-based SLAM for multiple times of day

Appearance-based mapping and localisation is especially challenging when separate processes of mapping and localisation occur at different times of day. The problem is exacerbated in the outdoors where continuous change in sun angle can drastically affect the appearance of a scene. We confront this challenge by fusing the probabilistic local feature based data association method of FAB-MAP with the pose cell filtering and experience mapping of RatSLAM. We evaluate the effectiveness of our amalgamation of methods using five datasets captured throughout the day from a single camera driven through a network of suburban streets. We show further results when the streets are re-visited three weeks later, and draw conclusions on the value of the system for lifelong mapping.

Cascading appearance-based features for visual voice activity detection

The detection of voice activity is a challenging problem, especially when the level of acoustic noise is high. Most current approaches only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to overcome this is to use the visual modality. The current state-of-the-art visual feature extraction technique is one that uses a cascade of visual features (i.e. 2D-DCT, feature mean normalisation, interstep LDA). In this paper, we investigate the effectiveness of this technique for the task of visual voice activity detection (VAD), and analyse each stage of the cascade and quantify the relative improvement in performance gained by each successive stage. The experiments were conducted on the CUAVE database and our results highlight that the dynamics of the visual modality can be used to good effect to improve visual voice activity detection performance.

Effect of optical aberrations on the color appearance of small defocused lights

We investigated influences of optics and surround area on color appearance of defocused, small narrow band photopic lights (1’ arc diameter, λmax 510 - 628 nm) centered within a black annulus and surrounded by a white field. Participants included seven normal trichromats with L- or M-cone biased ratios. We controlled chromatic aberration with elements of a Powell achromatizing lens and corrected higher-order aberrations with an adaptive-optics system. Longitudinal chromatic aberrations, but not monochromatic aberrations, are involved in changing appearance of small lights with defocus. Surround field structure is important because color changes were not observed when lights were presented on a uniform white surround.

Bayesian filtering over compressed appearance states

This paper presents a framework for performing real-time recursive estimation of landmarks’ visual appearance. Imaging data in its original high dimensional space is probabilistically mapped to a compressed low dimensional space through the definition of likelihood functions. The likelihoods are subsequently fused with prior information using a Bayesian update. This process produces a probabilistic estimate of the low dimensional representation of the landmark visual appearance. The overall filtering provides information complementary to the conventional position estimates which is used to enhance data association. In addition to robotics observations, the filter integrates human observations in the appearance estimates. The appearance tracks as computed by the filter allow landmark classification. The set of labels involved in the classification task is thought of as an observation space where human observations are made by selecting a label. The low dimensional appearance estimates returned by the filter allow for low cost communication in low bandwidth sensor networks. Deployment of the filter in such a network is demonstrated in an outdoor mapping application involving a human operator, a ground and an air vehicle.

Continuous appearance-based trajectory SLAM

This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The proposed system, dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM), represents location as a probability distribution along a trajectory, and represents appearance continuously over the trajectory rather than at discrete locations. The distribution is evaluated using a Rao-Blackwellised particle filter, which weights particles based on local appearance and odometric similarity and explicitly models both the likelihood of revisiting previous locations and visiting new locations. A modified resampling scheme counters particle deprivation and allows loop closure updates to be performed in constant time regardless of map size. We compare the performance of CAT-SLAM to FAB-MAP (an appearance-only SLAM algorithm) in an outdoor environment, demonstrating a threefold increase in the number of correct loop closures detected by CAT-SLAM.

Fourier active appearance models

Gaining invariance to camera and illumination variations has been a well investigated topic in Active Appearance Model (AAM) fitting literature. The major problem lies in the inability of the appearance parameters of the AAM to generalize to unseen conditions. An attractive approach for gaining invariance is to fit an AAM to a multiple filter response (e.g. Gabor) representation of the input image. Naively applying this concept with a traditional AAM is computationally prohibitive, especially as the number of filter responses increase. In this paper, we present a computationally efficient AAM fitting algorithm based on the Lucas-Kanade (LK) algorithm posed in the Fourier domain that affords invariance to both expression and illumination. We refer to this as a Fourier AAM (FAAM), and show that this method gives substantial improvement in person specific AAM fitting performance over traditional AAM fitting methods.

Geometry vs appearance for discriminating between posed and spontaneous emotions

Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.

Loop closure detection on a suburban road network using a continuous appearance-based trajectory

This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or performing 3D map construction. For loop closure detection CAT-SLAM updates in constant time regardless of map size. We evaluate the effectiveness of CAT-SLAM on a 16km outdoor road network and determine its loop closure performance relative to FAB-MAP. CAT-SLAM recognizes 3 times the number of loop closures for the case where no false positives occur, demonstrating its potential use for robust loop closure detection in large environments.