Query: Implementation of a 3 D pose estimation algorithm

Relevant passages:
Fast Feature Pyramids for Object Detection <=SEP=> Multi-resolution image features may be approximated via extrapolation from nearby scales, rather than being computed explicitly. This fundamental insight allows us to design object detection algorithms that are as accurate, and considerably faster, than the state-of-the-art. The computational bottleneck of many modern detectors is the computation of features at every scale of a finely-sampled image pyramid. Our key insight is that one may compute finely sampled feature pyramids at a fraction of the cost, without sacrificing performance: for a broad family of features we find that features computed at octave-spaced scale intervals are sufficient to approximate features on a finely-sampled pyramid. Extrapolation is inexpensive as compared to direct feature computation. As a result, our approximation yields considerable speedups with negligible loss in detection accuracy. We modify three diverse visual recognition systems to use fast feature pyramids and show results on both pedestrian detection (measured on the Caltech, INRIA, TUD-Brussels and ETH data sets) and general object detection (measured on the PASCAL VOC). The approach is general and is widely applicable to vision algorithms requiring fine-grained multi-scale analysis. Our approximation is valid for images with broad spectra (most natural images) and fails for images with narrow band-pass spectra (e.g., periodic textures).

Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces <=SEP=> We propose a novel and fast multiscale feature detection and description approach that exploits the benefits of nonlinear scale spaces. Previous attempts to detect and describe features in nonlinear scale spaces are highly time consuming due to the computational burden of creating the nonlinear scale space. In this paper we propose to use recent numerical schemes called Fast Explicit Diffusion (FED) embedded in a pyramidal framework to dramatically speed-up feature detection in nonlinear scale spaces. In addition, we introduce a Modified-Local Difference Binary (M-LDB) descriptor that is highly efficient, exploits gradient information from the nonlinear scale space, is scale and rotation invariant and has low storage requirements. We present an extensive evaluation that shows the excellent compromise between speed and performance of our approach compared to state-of-the-art methods such as BRISK, ORB, SURF, SIFT and KAZE.

Polynomial Eigenvalue Solutions to the 5-pt and 6-pt Relative Pose Problems <=SEP=> In this paper we provide new fast and simple solutions to two important minimal problems in computer vision, the five-point relative pose problem and the six-point focal length problem. We show that these two problems can easily be formulated as polynomial eigenvalue problems of degree three and two and solved using standard efficient numerical algorithms. Our solutions are somewhat more stable than state-of-the-art solutions by Nister and Stewenius and are in some sense more straightforward and easier to implement since polynomial eigenvalue problems are well studied with many efficient and robust algorithms available. The quality of the solvers is demonstrated in experiments 1.

Object Recognition from Local Scale-Invariant Features <=SEP=> Proc. of the International Conference on Computer Vision, Corfu (Sept. 1999) An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and affine or 3D projection. These features share similar properties with neurons in inferior temporal cortex that are used for object recognition in primate vision. Features are efficiently detected through a staged filtering approach that identifies stable points in scale space. Image keys are created that allow for local geometric deformations by representing blurred image gradients in multiple orientation planes and at multiple scales. The keys are used as input to a nearest-neighbor indexing method that identifies candidate object matches. Final verification of each match is achieved by finding a low-residual least-squares solution for the unknown model parameters. Experimental results show that robust object recognition can be achieved in cluttered partially-occluded images with a computation time of under 2 seconds.

Multi-image matching using multi-scale oriented patches <=SEP=> This paper describes a novel multi-view matching framework based on a new type of invariant feature. Our features are located at Harris corners in discrete scale-space and oriented using a blurred local gradient. This defines a rotationally invariant frame in which we sample a feature descriptor, which consists of an 8 /spl times/ 8 patch of bias/gain normalised intensity values. The density of features in the image is controlled using a novel adaptive non-maximal suppression algorithm, which gives a better spatial distribution of features than previous approaches. Matching is achieved using a fast nearest neighbour algorithm that indexes features based on their low frequency Haar wavelet coefficients. We also introduce a novel outlier rejection procedure that verifies a pairwise feature match based on a background distribution of incorrect feature matches. Feature matches are refined using RANSAC and used in an automatic 2D panorama stitcher that has been extensively tested on hundreds of sample inputs.

The Option-Critic Architecture <=SEP=> We first studied the behavior of the intra-option policy gradient algorithm when the initiation sets and subgoals are fixed by hand. In this case, options terminate with probability 0.9 in a hallway state and four of its incoming neighboring states. We chose to parametrize the intra-option policies using the softmax distribution with a one-hot encoding of state-action pairs as basis functions. Learning both intra-option policies and terminations

Dark vs. Dim Silicon and Near-Threshold Computing <=SEP=> Due to limited scaling of supply voltage, power density is expected to grow in future technology nodes. This increasing power density potentially limits the number of transistors switching at full speed in the future. Near-threshold operation can increase the number of simultaneously active cores, at the expense of much lower operating frequency (“dim silicon”). Although promising to increase overall throughput, dim cores suffer from diminishing returns as the number of cores increases. At this point, hardware accelerators become more efficient alternatives. To explore such a broad design space, we have developed a framework called Lumos to analytically quantify the performance limits of many-core, heterogeneous systems operating at near-threshold voltage. Lumos augments Amdahl’s Law with detailed scaling of frequency and power, calibrated by circuit-level simulations using a modified Predictive Technology Model (PTM) and factors in effects of process variations. While our results show that dim cores do indeed boost throughput, even in the presence of process variations, significant benefits are only achieved in applications with very high parallelism or with novel architectures to mitigate variation. A more beneficial 1 and scalable approach is to use accelerators. However, reconfigurable logic that supports a variety of accelerators is more beneficial than a dedicated, fixed-logic accelerator, unless 1) the dedicated kernel has overwhelming coverage across applications (e.g. twice as large as the total of all others), or 2) the speedup of the dedicated accelerator over the reconfigurable equivalent is significant (e.g. 10x-50x).

AmiGO: online access to ontology and annotation data <=SEP=> AmiGO is a web application that allows users to query, browse and visualize ontologies and related gene product annotation (association) data. AmiGO can be used online at the Gene Ontology (GO) website to access the data provided by the GO Consortium; it can also be downloaded and installed to browse local ontologies and annotations. AmiGO is free open source software developed and maintained by the GO Consortium.

A GLOBAL MEASURE OF PERCEIVED STRESS <=SEP=> Aim: To evaluate validity of the Greek version of a global measure of perceived stress PSS−14 (Perceived Stress Scale – 14 item). Materials and Methods: The original PSS−14 (theoretical range 0−56) was translated into Greek and then back-translated. One hundred men and women (39±10 years old, 40 men) participated in the validation process. Firstly, participants completed the Greek PSS−14 and, then they were interviewed by a psychologist specializing in stress management. Cronbach’s alpha (α) evaluated internal consistency of the measurement, whereas Kendall’s tau-b and Bland & Altman methods assessed consistency with the clinical evaluation. Exploratory and Confirmatory Factor analyses were conducted to reveal hidden factors within the data and to confirm the two-dimensional character of the scale. Results: Mean (SD) PSS−14 score was 25(7.9). Strong internal consistency (Cronbach’s α = 0.847) as well as moderate-to-good concordance between clinical assessment and PSS−14 (Kendall’s tau-b = 0.43, p<0.01) were observed. Two factors were extracted. Factor one explained 34.7% of variability and was heavily laden by positive items, and factor two that explained 10.6% of the variability by negative items. Confirmatory factor analysis revealed that the model with 2 factors had chi-square equal to 241.23 (p<0.001), absolute fix indexes were good (i.e. GFI=0.733, AGFI=0.529), and incremental fix indexes were also adequate (i.e. NFI=0.89 and CFI=0.92). Conclusion: The developed Greek version of PSS−14 seems to be a valid instrument for the assessment of perceived stress in the Greek adult population living in urban areas; a finding that supports its local use in research settings as an evaluation tool measuring perceived stress, mainly as a risk factor but without diagnostic properties.

Stress and hippocampal plasticity. <=SEP=> The hippocampus is a target of stress hormones, and it is an especially plastic and vulnerable region of the brain. It also responds to gonadal, thyroid, and adrenal hormones, which modulate changes in synapse formation and dendritic structure and regulate dentate gyrus volume during development and in adult life. Two forms of structural plasticity are affected by stress: Repeated stress causes atrophy of dendrites in the CA3 region, and both acute and chronic stress suppresses neurogenesis of dentate gyrus granule neurons. Besides glucocorticoids, excitatory amino acids and N-methyl-D-aspartate (NMDA) receptors are involved in these two forms of plasticity as well as in neuronal death that is caused in pyramidal neurons by seizures and by ischemia. The two forms of hippocampal structural plasticity are relevant to the human hippocampus, which undergoes a selective atrophy in a number of disorders, accompanied by deficits in declarative episodic, spatial, and contextual memory performance. It is important, from a therapeutic standpoint, to distinguish between a permanent loss of cells and a reversible atrophy.

Conservative treatment of carpal tunnel syndrome: comparison between laser therapy and Fascial Manipulation(®). <=SEP=> The etiopathogenesis of Carpal Tunnel Syndrome (CTS) is multifactorial and most cases are classified as idiopathic (Thurston 2013). A randomized controlled trial was performed to compare the effectiveness of Fascial Manipulation(®) (FM) and Low-Level Laser Therapy (LLLT) for CTS. This prospective trial included 42 patients (70 hands with symptoms) with clinical and electroneuromyographic diagnosis of CTS. The patients were randomly assigned to receive multiple sessions of FM or multiple session of LLLT. The Visual Analogic Scale (VAS) and Boston Carpal Tunnel Questionnaire (BCTQ) were performed at baseline, end of treatment and after three months. The group that received FM showed a significant reduction in subjective pain perception and an increased function assessed by BCTQ at the end of the treatment and follow-up. The group that received LLLT showed an improvement in the BCTQ at the end of the treatment but the improvement level was not sustained at the three month follow-up. FM is a valid alternative treatment for CTS.

An OFDMA based multiple access protocol with QoS guarantee for next generation WLAN <=SEP=> To provide better QoS guarantee for the next generation WLAN, IEEE 802.11ax task group is founded in March 2014. As a promising technology to accommodate multiple nodes concurrent transmissions in dense deployment scenario, orthogonal frequency division multiple access (OFDMA) will be adopted in IEEE 802.11ax with great possibility. In this paper, an OFDMA based multiple access protocol with QoS guarantee is proposed for the next generation WLAN. Firstly, a redundant access mechanism is given to increase the access success probability of the video traffic where the video stations can concurrently send multiple RTS packets in multiple subchannels. Secondly, a priority based resource allocation scheme is presented to let AP allocate more resources to the video stations. Simulation results show that our protocol outperforms the existing OFDMA based multiple access for IEEE 802.11ax (OMAX) protocol in terms of delay and delay jitter of video traffic in dense deployment scenario.

10.6 THz figure-of-merit phase-change RF switches with embedded micro-heater <=SEP=> We report on GeTe-based phase-change RF switches with embedded micro-heater for thermal switching. With heater parasitics reduced, GeTe RF switches show onstate resistance of 0.05 ohm*mm and off-state capacitance of 0.3 pF/mm. The RF switch figure-of-merit is estimated to be 10.6 THz, which is about 15 times better than state-of-the-art silicon-on-insulator switches. With on-state resistance of 1 ohm and off-state capacitance of 15 fF, RF insertion loss was measured at <;0.2 dB, and isolation was >25 dB at 20 GHz, respectively. RF power handling was >5.6 W for both onand off-state of GeTe.

The Mediator complex: a central integrator of transcription <=SEP=> The RNA polymerase II (Pol II) enzyme transcribes all protein-coding and most non-coding RNA genes and is globally regulated by Mediator — a large, conformationally flexible protein complex with a variable subunit composition (for example, a four-subunit cyclin-dependent kinase 8 module can reversibly associate with it). These biochemical characteristics are fundamentally important for Mediator's ability to control various processes that are important for transcription, including the organization of chromatin architecture and the regulation of Pol II pre-initiation, initiation, re-initiation, pausing and elongation. Although Mediator exists in all eukaryotes, a variety of Mediator functions seem to be specific to metazoans, which is indicative of more diverse regulatory requirements.

From information security to ... business security? <=SEP=> This short opinion paper argues that information security, the discipline responsible for protecting a company's information assets against business risks, has now become such a crucial component of good Corporate Governance, that it should rather be called Business Security instead of Information Security. During the last year or two, driven by developments in the field of Corporate Governance, including IT Governance, it became apparent that the scope of Information Security is much wider than just (directly) protecting the data, information and software of a business. Such data, information and software had become invaluable assets of the business as a whole, and not properly protecting this information could have profound business and legal implications. Basically, the data and information of the business became its 'life blood', and compromising this life blood, could kill the business. Executive Management and Boards started realizing that Information Security Governance was becoming their direct responsibility, and that serious personal consequences, specifically legally, could flow from ignoring information security. Information security governance had become an

Support Vector Machines For Synthetic Aperture Radar Automatic Target Recognition <=SEP=> Algorithms that produce classifiers with large margins, such as support vector machines (SVMs), AdaBoost, etc. are receiving more and more attention in the literature. This paper presents a real application of SVMs for synthetic aperture radar automatic target recognition (SAR/ATR) and compares the result with conventional classifiers. The SVMs are tested for classification both in closed and open sets (recognition). Experimental results showed that SVMs outperform conventional classifiers in target classification. Moreover, SVMs with the Gaussian kernels are able to form a local " bounded " decision region around each class that presents better rejection to confusers.

A SiC-Based High-Efficiency Isolated Onboard PEV Charger With Ultrawide DC-Link Voltage Range <=SEP=> In LLC-based onboard battery charging architectures used in plug-in electric vehicles (PEV), the dc link voltage can be actively regulated to follow the battery pack voltage so that the LLC converter can operate in proximity of resonant frequency and achieve high efficiencies over the wide range of battery pack voltage. However, conventional boost-type power factor correction (PFC) converters are unable to provide ultrawide dc link voltages since their output voltages should always be larger than their input voltages. This paper proposes a Silicon Carbide (SiC)-based onboard PEV charger using single-ended primary-inductor converter (SEPIC) PFC converter followed by an isolated LLC resonant converter. With the proposed charger architecture, the SEPIC PFC converter is able to provide an ultrawide range for dc link voltage, and consequently enhance the efficiency of the LLC stage by ensuring operation in proximity of resonant frequency. A 1-kW SiC-based prototype is designed to validate the proposed idea. The experimental result shows that the SEPIC PFC converter achieves unity power factor, 2.72% total harmonic distortion, and 95.3% peak conversion efficiency. The LLC  converter achieves 97.1% peak efficiency and always demonstrates a very high efficiency across the ultrawide dc-link voltage range. The overall efficiency of the charger is 88.5% to 93.5% from 20% of the rated load to full load.

EKG-based key agreement in Body Sensor Networks <=SEP=> Preserving a person's privacy in an efficient manner is very important for critical, life-saving infrastructures like body sensor networks (BSN). This paper presents a novel key agreement scheme which allows two sensors in a BSN to agree to a common key generated using electrocardiogram (EKG) signals. This EKG-based key agreement (EKA) scheme aims to bring the "plug-n-play" paradigm to BSN security whereby simply deploying sensors on the subject can enable secure communication, without requiring any form of initialization such as pre-deployment. Analysis of the scheme based on real EKG data (obtained from MIT PhysioBank database) shows that keys resulting from EKA are: random, time variant, can be generated based on short-duration EKG measurements, identical for a given subject and different for separate individuals.

Zero-Current Switching Switched-Capacitor Zero-Voltage-Gap Automatic Equalization System for Series Battery String <=SEP=> The series battery string or supercapacitor string automatic equalization system based on quasi-resonant switched-capacitor converter is presented in this paper. It realizes the zero-voltage gap between cells and allows maximum energy recovery in a series battery system or supercapacitor system. It not only inherits the advantage of conventional switched-capacitor battery cell balancing system, but also overcomes the drawback of conduction loss, switching loss, and finite voltage difference among battery cells. All switches are MOSFET and controlled by just a pair of complementary signals in synchronous trigger pattern and the resonant tanks operate alternatively between the two states of charging and discharging. Zero-current switching and zero-voltage gap are achieved in this paper. Different resonant tank designs can meet the needs of different balancing time to meet the needs of different energy storage devices. Experimental results indicate that the efficiency of the system is high exceeding 98%. The system is very suitable for balancing used in battery management system.

Wireless access monitoring and control system based on digital door lock <=SEP=> We propose a novel wireless access monitoring and control system based on the digital door lock, which is explosively used as a digital consumer device. Digital door lock is an electronic locking system operated by the combination of digital key, security password or number codes. This paper presents a prototype of the proposed system and shows a scheme for the implementation. To implement the system with ZigBee network protocol, four types of modules are developed, ZigBee module, digital door lock module, human detection module, and ZigBee relay module. ZigBee module is designed to support wireless sensor network and also used for the ZigBee tag to identify the access objects. Digital door lock module is implemented as a digital consumer device to control the access system as well as locking system. It is very convenient system for the consumers and has extensible and flexible characteristics. That is, it can be used as a home security system by the ZigBee network with additional sensor devices. Therefore, it can be a good practical product for the realization of an access monitoring and control system. It also can be applied to the real market for home networking system. Furthermore, the system can be extended to another service such as a connection between mobile phone and home networking system.

Code Conjurer: Pulling Reusable Software out of Thin Air <=SEP=> For many years, the IT industry has sought to accelerate the software development process by assembling new applications from existing software assets. However, true component-based reuse of the form Douglas Mcllroy envisaged in the 1960s is still the exception rather than the rule, and most of the systematic software reuse practiced today uses heavyweight approaches such as product-line engineering or domain-specific frameworks. By component, we mean any cohesive and compact unit of software functionality with a well-defined interface - from simple programming language classes to more complex artifacts such as Web services and Enterprise JavaBeans.

Synthetic aperture radar at millimeter wavelength for UAV surveillance applications <=SEP=> The airborne monitoring of scenes using unmanned aircrafts is becoming increasingly important. Several types of airborne sensors - in the optical, infrared or millimeter wave spectrum - are available for the different platforms. Beside the all-weather suitability of the sensors, the deployment scenarios, often also demand for the ability to look through dust clouds, smoke, and fog. The only sensor, which is capable to cope with such environmental restrictions and is able to deliver high-resolution images, is the synthetic aperture radar (SAR). In this paper we focus on miniaturized SAR systems which were developed and optimized for utilization in a UA V (unmanned aerial vehicle) with a low loading capacity. This not only requires a compact and light radar sensor but the processing also has to cope with the unstable flight conditions of a small aircraft. Therefore, a high-precision inertial measurement unit (IMU) and motion compensating SAR-algorithms are needed. Thanks to the utilization of a high transmit frequency of either 35 GHz or 94 GHz, the sensors are suitable for the detection of small-scale objects. A very high resolution of 15 cm × 15 cm can be achieved when using modern FMCW (frequency modulated continuous wave) generation with a high bandwidth (up to 1 GHz) in combination with small antennas.

Effect of rule weights in fuzzy rule-based classification systems <=SEP=> This paper examines the effect of rule weights in fuzzy rule-based classification systems. Each fuzzy IF–THEN rule in our classification system has antecedent linguistic values and a single consequent class. We use a fuzzy reasoning method based on a single winner rule in the classification phase. The winner rule for a new pattern is the fuzzy IF–THEN rule that has the maximum compatibility grade with the new pattern. When we use fuzzy IF–THEN rules with certainty grades (i.e., rule weights), the winner is determined as the rule with the maximum product of the compatibility grade and the certainty grade. In this paper, the effect of rule weights is illustrated by drawing classification boundaries using fuzzy IF–THEN rules with/without certainty grades. It is also shown that certainty grades play an important role when a fuzzy rule-based classification system is a mixture of general rules and specific rules. Through computer simulations, we show that comprehensible fuzzy rule-based systems with high classification performance can be designed without modifying the membership functions of antecedent linguistic values when we use fuzzy IF–THEN rules with certainty grades.

FindingHuMo: Real-Time Tracking of Motion Trajectories from Anonymous Binary Sensing in Smart Environments <=SEP=> In this paper we have proposed and designed FindingHuMo (Finding Human Motion), a real-time user tracking system for Smart Environments. FindingHuMo can perform device-free tracking of multiple (unknown and variable number of) users in the Hallway Environments, just from non-invasive and anonymous (not user specific) binary motion sensor data stream. The significance of our designed system are as follows: (a) fast tracking of individual targets from binary motion data stream from a static wireless sensor network in the infrastructure. This needs to resolve unreliable node sequences, system noise and path ambiguity, (b) Scaling for multi-user tracking where user motion trajectories may crossover with each other in all possible ways. This needs to resolve path ambiguity to isolate overlapping trajectories, FindingHumo applies the following techniques on the collected motion data stream: (i) a proposed motion data driven adaptive order Hidden Markov Model with Viterbi decoding (called Adaptive-HMM), and then (ii) an innovative path disambiguation algorithm (called CPDA). Using this methodology the system accurately detects and isolates motion trajectories of individual users. The system performance is illustrated with results from real-time system deployment experience in a Smart Environment.

On the role of color in the perception of motion in animated visualizations <=SEP=> Although luminance contrast plays a predominant role in motion perception, significant additional effects are introduced by chromatic contrasts. In this paper, relevant results from psychophysical and physiological research are described to clarify the role of color in motion detection. Interpreting these psychophysical experiments, we propose guidelines for the design of animated visualizations, and a calibration procedure that improves the reliability of visual motion representation. The guidelines are applied to examples from texture-based flow visualization, as well as graph and tree visualization.

Forward models and passive psychotic symptoms <=SEP=> Pickering and Clark (2014) present two ways of viewing the role of forward models in human cognition: the auxiliary forward model (AFM) account and the integral forward model (IFM) account. The AFM account “assumes a dedicated prediction mechanism implemented by additional circuitry distinct from the core mechanisms of perception and action” (p. 451). The standard AFM account exploits a corollary discharge from the motor command in order to compute the sensory consequences of the action. In contrast, on the IFM account, “perception itself involves the use of a forward (generative) model, whose role is to construct the incoming sensory signal ‘from the top down”’ (p. 453). Furthermore, within this account, motor commands are dispensed with: they are predictions that are fulfilled by movement as part of the prediction error minimization that is taken to govern all aspects of cognition (Adams et al., 2013). Pickering and Clark present two “testing grounds” for helping us adjudicate between IFMs and AFMs, which are committed to the idea, derived from Pickering’s own work, that one predicts others in a way that is similar to the way that one predicts oneself. Although I like this “prediction by simulation” account, in this commentary, I want to emphasize that neither the IFM nor the AFM accounts are necessarily wedded to it. A less committal, and hence perhaps more compelling, testing ground is to be found in psychotic symptoms, and the capacity of the two frameworks to account for them. Indeed, using psychosis to illustrate forward modelling is not new: the inability to self-tickle was taken to be convincing data for the presence of forward models (viewed, by default, within an AFM account), and in particular for problems with them in patients with diagnoses of schizophrenia (Frith et al., 2000). The AFM account has been used more generally to explain symptoms of schizophrenia. Something goes wrong with the generation of the forward model, and so the sensory consequences of selfgenerated stimuli are poorly predicted, and hence fail to be attenuated, and are, ultimately, misattributed to an external source. Although most have accepted this for delusions of control, some have questioned the application of this model to passive symptoms (Stephens and Graham, 2000), namely those which do not involve action, such as auditory verbal hallucinations (AVHs). If the symptoms of schizophrenia are explainable in terms of problems with an AFM, and this is constructed out of a motor command, then non-motoric (“passive”) symptoms cannot be so explained. One move has been to keep working within the AFM framework but claim that “passive” symptoms merely look passive: they are actually “active.” Several theorists (e.g., Jones and Fernyhough, 2007) have attempted to explain AVHs in terms of inner speech misattribution, where inner speech is taken to involve motoric elements. This motoric involvement has been empirically supported by several electromyographical (EMG) studies (which measured muscular activity during inner speech) some of which date as far back as the early 1930s (Jacobsen, 1931). Later experiments made the connection between inner speech and AVH, showing that similar muscular activation is involved in healthy inner speech and AVH (Gould, 1948). The involvement of motoric elements in both inner speech and in AVH is further supported by findings (Gould, 1950) showing that when subjects hallucinated, subvocalizations occurred which could be picked up with a throat microphone. That these subvocalizations were causally responsible for the inner speech allegedly implicated in AVHs, and not just echoing it, was suggested by data (Bick and Kinsbourne, 1987) demonstrating that if people experiencing hallucinations opened their mouths wide, stopping vocalizations, then the majority of AVHs stopped. However, this does not seem to capture all AVH subtypes. For example, Dodgson and Gordon (2009) convincingly present “hypervigilance hallucinations,” which are not based on self-generated stimuli, but constitute hypervigilant boosting and molding of external stimuli. As I have argued (Wilkinson, 2014) recently, one can account for both inner speech-based and hypervigilance hallucinations, within an IFM framework (although I called it a “Predictive Processing Framework”). Since it is good practice to support models that accommodate more phenomena, assuming (as seems plausible) that hypervigilance hallucinations are a genuine subtype of AVH, the IFM account is preferable to the AFM account. In conclusion, although I agree with Pickering and Clark that the IFM account is preferable, I do so on the basis of a

Finding objects for blind people based on SURF features <=SEP=> Nowadays computer vision technology is helping the visually impaired by recognizing objects in their surroundings. Unlike research of navigation and wayfinding, there are no camera-based systems available in the market to find personal items for the blind. This paper proposes an object recognition method to help blind people find missing items using Speeded-Up Robust Features (SURF). SURF features can extract distinctive invariant features that can be utilized to perform reliable matching between different images in multiple scenarios. These features are invariant to image scale, translation, rotation, illumination, and partial occlusion. The proposed recognition process begins by matching individual features of the user queried object to a database of features with different personal items which are saved in advance. Experiment results demonstrate the effectiveness and efficiency of the proposed method.

UAV vision aided positioning system for location and landing <=SEP=> The research and use of UAVs (Unmanned Aerial Vehicles) have grown in attention and new ideas in the last couple of decades, mainly due to technology improvement of its construction parts, sensors and controllers. When it comes to its autonomous behavior, robust techniques make themselves necessary to assure the security of the aircraft and people around it. This work presents the use of computer vision techniques to improve the positioning of a quadrotor UAV in the landing moment, adding security and precision, overcoming intrinsic errors of other positioning sensors, such as GPS. A landmark was built to be detected by the camera with contour detection, image thresholding and other mathematical techniques in order to obtain fast, simple and robust processing and results. A GoPro camera model was used with a developed algorithm to remove the image distortion. With this set up, the vehicle can be programmed to develop any mission, with this works control algorithm taking part with the vision aided positioning in the landing moment. The quadrotor was conceived and built at the GRIn (Grupo de Robtica Inteligente) laboratory at UFJF (Juiz de Fora Federal University), and uses open source code for its control, with Mavlink communication protocol to exchange messages with the vision-based control algorithm for mission and landing. This algorithm was developed in Python language, and is in charge of image characteristics segmentation, extracting distances and altitude from the data. The control commands are sent to the quadrotor using the mentioned protocol. The system is structured with a remote laptop connected with a serial port to the quadrotor, and a router transmits messages back and forth among the GCS (Ground Control Station, on the laptop) and the high-level control algorithm (mission planning and vision based control) through TCP ports to the quadrotor itself. The camera is connected via Wi-Fi built-in network to the laptop, so all the image processing is done inside the last one. The results obtained in outdoor tests show the efficacy and fast processing of the vision methods and ensure safety in the landing moment. Furthermore, the positioning techniques can be extended to other UAV applications, such as transmission lines and utility equipment inspection and monitoring. Future works look forward to embedding the process in a companion board attached to the UAV, so the process would become automatic and the risk of communication interference and lost heavily reduced.

On semi-supervised linear regression in covariate shift problems <=SEP=> Semi-supervised learning approaches are trained using the full training (labeled) data and available testing (unlabeled) data. Demonstrations of the value of training with unlabeled data typically depend on a smoothness assumption relating the conditional expectation to high density regions of the marginal distribution and an inherent missing completely at random assumption for the labeling. So-called covariate shift poses a challenge for many existing semi-supervised or supervised learning techniques. Covariate shift models allow the marginal distributions of the labeled and unlabeled feature data to differ, but the conditional distribution of the response given the feature data is the same. An example of this occurs when a complete labeled data sample and then an unlabeled sample are obtained sequentially, as it would likely follow that the distributions of the feature data are quite different between samples. The value of using unlabeled data during training for the elastic net is justified geometrically in such practical covariate shift problems. The approach works by obtaining adjusted coefficients for unlabeled prediction which recalibrate the supervised elastic net to compromise: (i) maintaining elastic net predictions on the labeled data with (ii) shrinking unlabeled predictions to zero. Our approach is shown to dominate linear supervised alternatives on unlabeled response predictions when the unlabeled feature data are concentrated on a low dimensional manifold away from the labeled data and the true coefficient vector emphasizes directions away from this manifold. Large variance of the supervised predictions on the unlabeled set is reduced more than the increase in squared bias when the unlabeled responses are expected to be small, so an improved compromise within the bias-variance tradeoff is the rationale for this performance improvement. Performance is validated on simulated and real data.

VIDEO GAMES: PERSPECTIVE, POINT-OF-VIEW, AND IMMERSION <=SEP=> of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Arts VIDEO GAMES: PERSPECTIVE, POINT-OF-VIEW, AND IMMERSION By Laurie N. Taylor May 2002 Chair: Dr. Terry Harpold Department: English Presently, video game designers, players, and often even video game theorists approach the representation of point-of-view in video games as intuitive and uncomplicated. Drawing on the current critical work on video games, theories of immersion and engagement, and theories of human-computer-interaction, I question the significance of optical perspective in video games in terms of player point-of-view. Because video games are an experiential medium, critical study of video games must include the study of the diegetic, visual-auditory, interface, and experiential (often termed interactive or participatory) aspects of video game play. Through an analysis of the various points-of-view within different games and the differing points-of-view within a single game, I attempt to delineate the differences both in the creation of the experiential game space and in the possibilities for immersion within the game space. For this, I delimit two types of immersion: diegetic immersion, which corresponds to immersion in the game, and intra-diegetic or situated immersion, which corresponds to immersion