Fast power line detection and localization using steerable filter for active UAV guidance

In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

In vitro and in vivo studies on protease-activated receptor-2

Protease-activated receptor-2 (PAR2) is a G protein coupled receptor (GPCR) that is activated by proteolytic cleavage of its amino terminal domain by trypsin-like serine proteases. Cleavage of this receptor exposes a neoepitope, termed the tethered ligand (TL), which binds intramolecularly within the receptor to stimulate signal transduction via coupled G proteins. PAR2-mediated signal transduction is also experimentally stimulated by hexapeptides (agonist peptides; APs) that are homologous to the TL sequence. Due to the irreversible nature of PAR2 proteolysis, downstream signal transduction is tightly regulated. Following activation, PAR2 is rapidly uncoupled from downstream signalling by the post-translational modifications phosphorylation and ubiquination which facilitate interactions with â- arrestin. This scaffolding protein couples PAR2 to the internalisation machinery initiating its desensitisation and trafficking through the early and late endosomes followed by receptor degradation. PAR2 is widely expressed in mammalian tissues with key roles for this receptor in cardiovascular, respiratory, nervous and musculoskeletal systems. This receptor has also been linked to pathological states with aberrant expression and signalling noted in several cancers. In prostate cancer, PAR2 signalling induces migration and proliferation of tumour derived cell lines, while elevated receptor expression has been noted in malignant tissues. Importantly, a role for this receptor has also been suggested in prostate cancer bone metastasis as coexpression of PAR2 and a proteolytic activator has been demonstrated by immunohistochemical analysis. Based on these data, the primary focus of this project has been on two aspects of PAR2 biology. The first is characterisation of cellular mechanisms that regulate PAR2 signalling and trafficking. The second aspect is the role of this receptor in prostate cancer bone metastasis. In addition, to permit these studies, it was first necessary to evaluate the specificity of the commercially available anti-PAR2 antibodies SAM11, C17, N19 and H99. The evaluation of the four commercially available antibodies was assessed using four techniques: immunoprecipitation; Western blot analysis; immunofluorescence; and flow cytometry. These approaches demonstrated that three of the antibodies efficiently detect ectopically expressed PAR2 by each of these techniques. A significant finding from this study was that N19 was the only antibody able to specifically detect N-glycosylated endogenous PAR2 by Western blot analysis. This analysis was performed on lysates from prostate cancer derived cell lines and tissue derived from wildtype and PAR2 knockout mice. Importantly, further evaluation demonstrated that this antibody also efficiently detects endogenous PAR2 at the cell surface by flow cytometry. The anti-PAR2 antibody N19 was used to explore the in vitro role of palmitoylation, the post-translational addition of palmitate, in PAR2 signalling, trafficking, cell surface expression and desensitization. Significantly, use of the palmitoylation inhibitor 2-bromopalmitate indicated that palmitate addition is important in trafficking of PAR2 endogenously expressed by prostate cancer cell lines. This was supported by palmitate labelling experiments using two approaches which showed that PAR2 stably expressed by CHO cells is palmitoylated and that palmitoylation occurs on cysteine 361. Another key finding from this study is that palmitoylation is required for optimal PAR2 signalling as Ca2+ flux assays indicated that in response to trypsin agonism, palmitoylation deficient PAR2 is ~9 fold less potent than wildtype receptor with a reduction of about 33% in the maximum signal induced via the mutant receptor. Confocal microscopy, flow cytometry and cell surface biotinylation analyses demonstrated that palmitoylation is required for efficient cell surface expression of PAR2. Importantly, this study also identified that palmitoylation of this receptor within the Golgi apparatus is required for efficient agonist-induced rab11amediated trafficking of PAR2 to the cell surface. Interestingly, palmitoylation is also required for receptor desensitization, as agonist-induced â-arrestin recruitment and receptor degradation were markedly reduced in CHO-PAR2-C361A cells compared with CHO-PAR2 cells. Collectively, these data provide new insights on the life cycle of PAR2 and demonstrate that palmitoylation is critical for efficient signalling, trafficking, cell surface localization and degradation of this receptor. This project also evaluated PAR2 residues involved in ligand docking. Although the extracellular loop (ECL)2 of PAR2 is known to be required for agonist-induced signal transduction, the binding pocket for receptor agonists remains to be determined. In silico homology modelling, based on a crystal structure for the prototypical GPCR rhodopsin, and ligand docking were performed to identify PAR2 transmembrane (TM) amino acids potentially involved in agonist binding. These methods identified 12 candidate residues that were mutated to examine the binding site of the PAR2 TL, revealed by trypsin cleavage, as well as of the soluble ligands 2f-LIGRLO-NH2 and GB110, which are both structurally based on the AP SLIGRLNH2. Ligand binding was evaluated from the impact of the mutated residues on PAR2-mediated calcium mobilisation. An important finding from these experiments was that mutation of residues Y156 and Y326 significantly reduced 2f-LIGRLO-NH2 and GB110 agonist activity. L307 was also important for GB110 activity. Intriguingly, mutation of PAR2 residues did not alter trypsin-induced signalling to the same extent as for the soluble agonists. The reason for this difference remains to be further examined by in silico and in vitro experimentation and, potentially, crystal structure studies. However, these findings identified the importance of TM domains in PAR2 ligand docking and will enhance the design of both PAR2 agonists and potentially agents to inhibit signalling (antagonists). The potential importance of PAR2 in prostate cancer bone metastasis was examined using a mouse model. In patients, prostate cancer bone metastases cause bone growth by disrupting bone homeostasis. In an attempt to mimic prostate cancer growth in bone, PAR2 responsive 22Rv1 prostate cancer cells, which form mixed osteoblastic and osteolytic lesions, were injected into the proximal aspect of mouse tibiae. A role for PAR2 was assessed by treating these mice with the recently developed PAR2 antagonist GB88. As controls, animals bearing intra-tibial tumours were also treated with vehicle (olive oil) or the prostate cancer chemotherapeutic docetaxel. The effect of these treatments on bone was examined radiographically and by micro-CT. Consistent with previous studies, 22Rv1 tumours caused osteoblastic periosteal spicule formation and concurrent osteolytic bone loss. Significantly, blockade of PAR2 signalling reduced the osteoblastic and osteolytic phenotype of 22Rv1 tumours in bone. No bone defects were detected in mice treated with docetaxel. These qualitative data will be followed in the future by quantitative micro-CT analysis as well as histology and histomorphometry analysis of already collected tissues. Nonetheless, these preliminary experiments highlight a potential role for PAR2 in prostate cancer growth in bone. In summary, in vitro studies have defined mechanisms regulating PAR2 activation, downstream signalling and trafficking and in vivo studies point to a potential role for this receptor in prostate cancer bone metastasis. The outcomes of this project are that a greater understanding of the biology of PAR2 may lead to the development of strategies to modulate the function of this receptor in disease.

Optimization of human papillomavirus type 16 (HPV-16) L1 expression in plants: Comparison of the suitability of different HPV-16 L1 gene variants and different cell-compartment localization

Virus-like particle-based vaccines for high-risk human papillomaviruses (HPVs) appear to have great promise; however, cell culture-derived vaccines will probably be very expensive. The optimization of expression of different codon-optimized versions of the HPV-16 L1 capsid protein gene in plants has been explored by means of transient expression from a novel suite of Agrobacterium tumefaciens binary expression vectors, which allow targeting of recombinant protein to the cytoplasm, endoplasmic reticulum (ER) or chloroplasts. A gene resynthesized to reflect human codon usage expresses better than the native gene, which expresses better than a plant-optimized gene. Moreover, chloroplast localization allows significantly higher levels of accumulation of L1 protein than does cytoplasmic localization, whilst ER retention was least successful. High levels of L1 (>17% total soluble protein) could be produced via transient expression: the protein assembled into higher-order structures visible by electron microscopy, and a concentrated extract was highly immunogenic in mice after subcutaneous injection and elicited high-titre neutralizing antibodies. Transgenic tobacco plants expressing a human codon-optimized gene linked to a chloroplast-targeting signal expressed L1 at levels up to 11% of the total soluble protein. These are the highest levels of HPV L1 expression reported for plants: these results, and the excellent immunogenicity of the product, significantly improve the prospects of making a conventional HPV vaccine by this means. © 2007 SGM.

Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph

The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.

Energy-efficient localization : GPS duty cycling with radio ranging

GPS is a commonly used and convenient technology for determining absolute position in outdoor environments, but its high power consumption leads to rapid battery depletion in mobile devices. An obvious solution is to duty cycle the GPS module, which prolongs the device lifetime at the cost of increased position uncertainty while the GPS is off. This article addresses the trade-off between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty while GPS is off. Empirical GPS and radio contact data from a large-scale animal tracking deployment is used to model node mobility, radio performance, and GPS. Because GPS takes a considerable, and variable, time after powering up before it delivers a good position measurement, we model the GPS behaviour through empirical measurements of two GPS modules. These models are then used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose strategies that use RSSI ranging and GPS back-offs to further reduce energy consumption. Results show that our combined strategies can cut node energy consumption by one third while still meeting application-specific positioning criteria.

Long exposure localization in darkness using consumer cameras

In this paper we demonstrate passive vision-based localization in environments more than two orders of magnitude darker than the current benchmark using a 100 webcam and a 500 camera. Our approach uses the camera’s maximum exposure duration and sensor gain to achieve appropriately exposed images even in unlit night-time environments, albeit with extreme levels of motion blur. Using the SeqSLAM algorithm, we first evaluate the effect of variable motion blur caused by simulated exposures of 132 ms to 10000 ms duration on localization performance. We then use actual long exposure camera datasets to demonstrate day-night localization in two different environments. Finally we perform a statistical analysis that compares the baseline performance of matching unprocessed greyscale images to using patch normalization and local neighbourhood normalization – the two key SeqSLAM components. Our results and analysis show for the first time why the SeqSLAM algorithm is effective, and demonstrate the potential for cheap camera-based localization systems that function across extreme perceptual change.

Gradual training of cascaded shape regression for facial landmark localization and pose estimation

Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.

Familial typical migraine: Significant linkage and localization of a gene to Xq24-28

In a previous study we found evidence for an X-linked genetic component for familial typical migraine in two large Australian white pedigrees, designated MF7 and MF14. Significant excess allele sharing was indicated by nonparametric linkage (NPL) analysis using GENEHUNTER (P=0.031 and P=0.012, respectively), with a combined analysis of the two pedigrees showing further increased evidence for linkage, producing a maximum NPL score of 2.87 (P=0.011 ) at DXS 1123 on Xq27. The present study was aimed at refining the localization of the migraine X-chromosomal component by typing additional markers, performing haplotype analysis and applying a more powerful technique in the analysis of linkage data from these two pedigrees. Results from the haplotype analyses, coupled with linkage analyses that produced a peak GENEHUNTER-PLUS LOD* score of 2.388 (P=0.0005), provide compelling evidence for the presence of a migraine susceptibility locus on chromosome Xq24-28.

Localization of Mineralocorticoid Receptors at Mammalian Synapses

In the brain, membrane associated nongenomic steroid receptors can induce fast-acting responses to ion conductance and second messenger systems of neurons. Emerging data suggest that membrane associated glucocorticoid and mineralocorticoid receptors may directly regulate synaptic excitability during times of stress when adrenal hormones are elevated. As the key neuron signaling interface, the synapse is involved in learning and memory, including traumatic memories during times of stress. The lateral amygdala is a key site for synaptic plasticity underlying conditioned fear, which can both trigger and be coincident with the stress response. A large body of electrophysiological data shows rapid regulation of neuronal excitability by steroid hormone receptors. Despite the importance of these receptors, to date, only the glucocorticoid receptor has been anatomically localized to the membrane. We investigated the subcellular sites of mineralocorticoid receptors in the lateral amygdala of the Sprague-Dawley rat. Immunoblot analysis revealed the presence of mineralocorticoid receptors in the amygdala. Using electron microscopy, we found mineralocorticoid receptors expressed at both nuclear including: glutamatergic and GABAergic neurons and extra nuclear sites including: presynaptic terminals, neuronal dendrites, and dendritic spines. Importantly we also observed mineralocorticoid receptors at postsynaptic membrane densities of excitatory synapses. These data provide direct anatomical evidence supporting the concept that, at some synapses, synaptic transmission is regulated by mineralocorticoid receptors. Thus part of the stress signaling response in the brain is a direct modulation of the synapse itself by adrenal steroids.

Quantitative proteomic approach to study subcellular localization of membrane proteins

As proteins within cells are spatially organized according to their role, knowledge about protein localization gives insight into protein function. Here, we describe the LOPIT technique (localization of organelle proteins by isotope tagging) developed for the simultaneous and confident determination of the steady-state distribution of hundreds of integral membrane proteins within organelles. The technique uses a partial membrane fractionation strategy in conjunction with quantitative proteomics. Localization of proteins is achieved by measuring their distribution pattern across the density gradient using amine-reactive isotope tagging and comparing these patterns with those of known organelle residents. LOPIT relies on the assumption that proteins belonging to the same organelle will co-fractionate. Multivariate statistical tools are then used to group proteins according to the similarities in their distributions, and hence localization without complete centrifugal separation is achieved. The protocol requires approximately 3 weeks to complete and can be applied in a high-throughput manner to material from many varied sources.

Swimmer localization from a moving camera

At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Localization of glucocorticoid receptors at postsynaptic membranes in the lateral amygdala

Glucocorticoids, released in high concentrations from the adrenal cortex during stressful experiences, bind to glucocorticoid receptors in nuclear and peri-nuclear sites in neuronal somata. Their classically known mode of action is to induce gene promoter receptors to alter gene transcription. Nuclear glucocorticoid receptors are particularly dense in brain regions crucial for memory, including memory of stressful experiences, such as the hippocampus and amygdala. While it has been proposed that glucocorticoids may also act via membrane bound receptors, the existence of the latter remains controversial. Using electron microscopy, we found glucocorticoid receptors localized to non-genomic sites in rat lateral amygdala, glia processes, presynaptic terminals, neuronal dendrites, and dendritic spines including spine organelles and postsynaptic membrane densities. The lateral nucleus of the amygdala is a region specifically implicated in the formation of memories for stressful experiences. These newly observed glucocorticoid receptor immunoreactive sites were in addition to glucocorticoid receptor immunoreactive signals observed using electron and confocal microscopy in lateral amygdala principal neuron and GABA neuron soma and nuclei, cellular domains traditionally associated with glucocorticoid immunoreactivity. In lateral amygdala, glucocorticoid receptors are thus also localized to non-nuclear-membrane translocation sites, particularly dendritic spines, where they show an affinity for postsynaptic membrane densities, and may have a specialized role in modulating synaptic transmission plasticity related to fear and emotional memory.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

An efficient and effective localization method for networked disjoint top-view cameras

Disjoint top-view networked cameras are among the most commonly utilized networks in many applications. One of the open questions for these cameras' study is the computation of extrinsic parameters (positions and orientations), named extrinsic calibration or localization of cameras. Current approaches either rely on strict assumptions of the object motion for accurate results or fail to provide results of high accuracy without the requirement of the object motion. To address these shortcomings, we present a location-constrained maximum a posteriori (LMAP) approach by applying known locations in the surveillance area, some of which would be passed by the object opportunistically. The LMAP approach formulates the problem as a joint inference of the extrinsic parameters and object trajectory based on the cameras' observations and the known locations. In addition, a new task-oriented evaluation metric, named MABR (the Maximum value of All image points' Back-projected localization errors' L2 norms Relative to the area of field of view), is presented to assess the quality of the calibration results in an indoor object tracking context. Finally, results herein demonstrate the superior performance of the proposed method over the state-of-the-art algorithm based on the presented MABR and classical evaluation metric in simulations and real experiments.