Wide-angle visual feature matching for outdoor localization

Wide-angle images exhibit significant distortion for which existing scale-space detectors such as the scale-invariant feature transform (SIFT) are inappropriate. The required scale-space images for feature detection are correctly obtained through the convolution of the image, mapped to the sphere, with the spherical Gaussian. A new visual key-point detector, based on this principle, is developed and several computational approaches to the convolution are investigated in both the spatial and frequency domain. In particular, a close approximation is developed that has comparable computation time to conventional SIFT but with improved matching performance. Results are presented for monocular wide-angle outdoor image sequences obtained using fisheye and equiangular catadioptric cameras. We evaluate the overall matching performance (recall versus 1-precision) of these methods compared to conventional SIFT. We also demonstrate the use of the technique for variable frame-rate visual odometry and its application to place recognition.

Improved Subject Identification in Surveillance Video using Super Resolution

The time consuming and labour intensive task of identifying individuals in surveillance video is often challenged by poor resolution and the sheer volume of stored video. Faces or identifying marks such as tattoos are often too coarse for direct matching by machine or human vision. Object tracking and super-resolution can then be combined to facilitate the automated detection and enhancement of areas of interest. The object tracking process enables the automatic detection of people of interest, greatly reducing the amount of data for super-resolution. Smaller regions such as faces can also be tracked. A number of instances of such regions can then be utilized to obtain a super-resolved version for matching. Performance improvement from super-resolution is demonstrated using a face verification task. It is shown that there is a consistent improvement of approximately 7% in verification accuracy, using both Eigenface and Elastic Bunch Graph Matching approaches for automatic face verification, starting from faces with an eye to eye distance of 14 pixels. Visual improvement in image fidelity from super-resolved images over low-resolution and interpolated images is demonstrated on a small database. Current research and future directions in this area are also summarized.

SeqSLAM : visual route-based navigation for sunny summer days and stormy winter nights

Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

All-environment visual place recognition with SMART

This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.

Functional MRI BOLD response to Tower of London performance of first-episode schizophrenia patients using cortical pattern matching

Due to its three-dimensional folding pattern, the human neocortex; poses a challenge for accurate co-registration of grouped functional; brain imaging data. The present study addressed this problem by; employing three-dimensional continuum-mechanical image-warping; techniques to derive average anatomical representations for coregistration; of functional magnetic resonance brain imaging data; obtained from 10 male first-episode schizophrenia patients and 10 age-matched; male healthy volunteers while they performed a version of the; Tower of London task. This novel technique produced an equivalent; representation of blood oxygenation level dependent (BOLD) response; across hemispheres, cortical regions, and groups, respectively, when; compared to intensity average co-registration, using a deformable; Brodmann area atlas as anatomical reference. Somewhat closer; association of Brodmann area boundaries with primary visual and; auditory areas was evident using the gyral pattern average model.; Statistically-thresholded BOLD cluster data confirmed predominantly; bilateral prefrontal and parietal, right frontal and dorsolateral; prefrontal, and left occipital activation in healthy subjects, while; patients’ hemispheric dominance pattern was diminished or reversed,; particularly decreasing cortical BOLD response with increasing task; difficulty in the right superior temporal gyrus. Reduced regional gray; matter thickness correlated with reduced left-hemispheric prefrontal/; frontal and bilateral parietal BOLD activation in patients. This is the; first study demonstrating that reduction of regional gray matter in; first-episode schizophrenia patients is associated with impaired brain; function when performing the Tower of London task, and supports; previous findings of impaired executive attention and working memory; in schizophrenia.

Dynamic Performance Measures for Object Tracking Systems

Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.

The impact of presbyopic spectacles and contact lenses on driving performance

Presbyopia affects individuals from the age of 45 years onwards, resulting in difficulty in accurately focusing on near objects. There are many optical corrections available including spectacles or contact lenses that are designed to enable presbyopes to see clearly at both far and near distances. However, presbyopic vision corrections also disturb aspects of visual function under certain circumstances. The impact of these changes on activities of daily living such as driving are, however, poorly understood. Therefore, the aim of this study was to determine which aspects of driving performance might be affected by wearing different types of presbyopic vision corrections. In order to achieve this aim, three experiments were undertaken. The first experiment involved administration of a questionnaire to compare the subjective driving difficulties experienced when wearing a range of common presbyopic contact lens and spectacle corrections. The questionnaire was developed and piloted, and included a series of items regarding difficulties experienced while driving under day and night-time conditions. Two hundred and fifty five presbyopic patients responded to the questionnaire and were categorised into five groups, including those wearing no vision correction for driving (n = 50), bifocal spectacles (BIF, n = 54), progressive addition lenses spectacles (PAL, n = 50), monovision (MV, n = 53) and multifocal contact lenses (MTF CL, n = 48). Overall, ratings of satisfaction during daytime driving were relatively high for all correction types. However, MV and MTF CL wearers were significantly less satisfied with aspects of their vision during night-time than daytime driving, particularly with regard to disturbances from glare and haloes. Progressive addition lens wearers noticed more distortion of peripheral vision, while BIF wearers reported more difficulties with tasks requiring changes in focus and those who wore no vision correction for driving reported problems with intermediate and near tasks. Overall, the mean level of satisfaction for daytime driving was quite high for all of the groups (over 80%), with the BIF wearers being the least satisfied with their vision for driving. Conversely, at night, MTF CL wearers expressed the least satisfaction. Research into eye and head movements has become increasingly of interest in driving research as it provides a means of understanding how the driver responds to visual stimuli in traffic. Previous studies have found that wearing PAL can affect eye and head movement performance resulting in slower eye movement velocities and longer times to stabilize the gaze for fixation. These changes in eye and head movement patterns may have implications for driving safety, given that the visual tasks for driving include a range of dynamic search tasks. Therefore, the second study was designed to investigate the influence of different presbyopic corrections on driving-related eye and head movements under standardized laboratory-based conditions. Twenty presbyopes (mean age: 56.1 ± 5.7 years) who had no experience of wearing presbyopic vision corrections, apart from single vision reading spectacles, were recruited. Each participant wore five different types of vision correction: single vision distance lenses (SV), PAL, BIF, MV and MTF CL. For each visual condition, participants were required to view videotape recordings of traffic scenes, track a reference vehicle and identify a series of peripherally presented targets while their eye and head movements were recorded using the faceLAB® eye and head tracking system. Digital numerical display panels were also included as near visual stimuli (simulating the visual displays of a vehicle speedometer and radio). The results demonstrated that the path length of eye movements while viewing and responding to driving-related traffic scenes was significantly longer when wearing BIF and PAL than MV and MTF CL. The path length of head movements was greater with SV, BIF and PAL than MV and MTF CL. Target recognition was less accurate when the near stimulus was located at eccentricities inferiorly and to the left, rather than directly below the primary position of gaze, regardless of vision correction type. The third experiment aimed to investigate the real world driving performance of presbyopes while wearing different vision corrections measured on a closed-road circuit at night-time. Eye movements were recorded using the ASL Mobile Eye, eye tracking system (as the faceLAB® system proved to be impractical for use outside of the laboratory). Eleven participants (mean age: 57.25 ± 5.78 years) were fitted with four types of prescribed vision corrections (SV, PAL, MV and MTF CL). The measures of driving performance on the closed-road circuit included distance to sign recognition, near target recognition, peripheral light-emitting-diode (LED) recognition, low contrast road hazards recognition and avoidance, recognition of all the road signs, time to complete the course, and driving behaviours such as braking, accelerating, and cornering. The results demonstrated that driving performance at night was most affected by MTF CL compared to PAL, resulting in shorter distances to read signs, slower driving speeds, and longer times spent fixating road signs. Monovision resulted in worse performance in the task of distance to read a signs compared to SV and PAL. The SV condition resulted in significantly more errors made in interpreting information from in-vehicle devices, despite spending longer time fixating on these devices. Progressive addition lenses were ranked as the most preferred vision correction, while MTF CL were the least preferred vision correction for night-time driving. This thesis addressed the research question of how presbyopic vision corrections affect driving performance and the results of the three experiments demonstrated that the different types of presbyopic vision corrections (e.g. BIF, PAL, MV and MTF CL) can affect driving performance in different ways. Distance-related driving tasks showed reduced performance with MV and MTF CL, while tasks which involved viewing in-vehicle devices were significantly hampered by wearing SV corrections. Wearing spectacles such as SV, BIF and PAL induced greater eye and head movements in the simulated driving condition, however this did not directly translate to impaired performance on the closed- road circuit tasks. These findings are important for understanding the influence of presbyopic vision corrections on vision under real world driving conditions. They will also assist the eye care practitioner to understand and convey to patients the potential driving difficulties associated with wearing certain types of presbyopic vision corrections and accordingly to support them in the process of matching patients to optical corrections which meet their visual needs.

Simulated cataract and low contrast stimuli impair cognitive performance in older adults : implications for neuropsychological assessment and everyday function

Objective: To investigate how age-related declines in vision (particularly contrast sensitivity), simulated using cataract-goggles and low-contrast stimuli, influence the accuracy and speed of cognitive test performance in older adults. An additional aim was to investigate whether declines in vision differentially affect secondary more than primary memory. Method: Using a fully within-subjects design, 50 older drivers aged 66-87 years completed two tests of cognitive performance - letter matching (perceptual speed) and symbol recall (short-term memory) - under different viewing conditions that degraded visual input (low-contrast stimuli, cataract-goggles, and low-contrast stimuli combined with cataract-goggles, compared with normal viewing). However, presentation time was also manipulated for letter matching. Visual function, as measured using standard charts, was taken into account in statistical analyses. Results: Accuracy and speed for cognitive tasks were significantly impaired when visual input was degraded. Furthermore, cognitive performance was positively associated with contrast sensitivity. Presentation time did not influence cognitive performance, and visual gradation did not differentially influence primary and secondary memory. Conclusion: Age-related declines in visual function can impact on the accuracy and speed of cognitive performance, and therefore the cognitive abilities of older adults may be underestimated in neuropsychological testing. It is thus critical that visual function be assessed prior to testing, and that stimuli be adapted to older adults' sensory capabilities (e.g., by maximising stimuli contrast).

Improving matching process in social network

Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

Matching cognitive styles to computer-based instruction : an approach for enhanced learning in electrical engineering

An approach aimed at enhancing learning by matching individual students' preferred cognitive styles to computer-based instructional (CBI) material is presented. This approach was used in teaching some components of a third-year unit in an electrical engineering course at the Queensland University of Technology. Cognitive style characteristics of perceiving and processing information were considered. The bimodal nature of cognitive styles (analytic/imager, analytic/verbalizer, wholist/imager and wholist/verbalizer) was examined in order to assess the full ramification of cognitive styles on learning. In a quasi-experimental format, students' cognitive styles were analysed by cognitive style analysis (CSA) software. On the basis of the CSA results the system defaulted students to either matched or mismatched CBI material. The consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. Analysing the differences between cognitive styles on individual test tasks also suggests that certain test tasks may better suit certain cognitive styles.

Improving the performance of facial expression recognition using dynamic, subtle and regional features

Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

Performance enhancement of smart antennas with reduced element spacing

This paper addresses the problem of degradations in adaptive digital beam-forming (DBF) systems caused by mutual coupling between array elements. The focus is on compact arrays with reduced element spacing and, hence, strongly coupled elements. Deviations in the radiation patterns of coupled and (theoretically) uncoupled elements can be compensated for by weight-adjustments in DBF, but SNR degradation due to impedance mismatches cannot be compensated for via signal processing techniques. It is shown that this problem can be overcome via the implementation of a RF-decoupling-network. SNR enhancement is achieved at the cost of a reduced frequency bandwidth and an increased sensitivity to dissipative losses in the antenna and matching network structure.

Probabilistic matching of image sets for video-based face recognition

We address the problem of face recognition on video by employing the recently proposed probabilistic linear discrimi-nant analysis (PLDA). The PLDA has been shown to be robust against pose and expression in image-based face recognition. In this research, the method is extended and applied to video where image set to image set matching is performed. We investigate two approaches of computing similarities between image sets using the PLDA: the closest pair approach and the holistic sets approach. To better model face appearances in video, we also propose the heteroscedastic version of the PLDA which learns the within-class covariance of each individual separately. Our experi-ments on the VidTIMIT and Honda datasets show that the combination of the heteroscedastic PLDA and the closest pair approach achieves the best performance.

Evaluation of image resolution and super-resolution on face recognition performance

While researchers strive to improve automatic face recognition performance, the relationship between image resolution and face recognition performance has not received much attention. This relationship is examined systematically and a framework is developed such that results from super-resolution techniques can be compared. Three super-resolution techniques are compared with the Eigenface and Elastic Bunch Graph Matching face recognition engines. Parameter ranges over which these techniques provide better recognition performance than interpolated images is determined.