964 resultados para Invariant Object Recognition
Resumo:
Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented
Resumo:
An interesting fact about language cognition is that stimulation involving incongruence in the merge operation between verb and complement has often been related to a negative event-related potential (ERP) of augmented amplitude and latency of ca. 400 ms - the N400. Using an automatic ERP latency and amplitude estimator to facilitate the recognition of waves with a low signal-to-noise ratio, the objective of the present study was to study the N400 statistically in 24 volunteers. Stimulation consisted of 80 experimental sentences (40 congruous and 40 incongruous), generated in Brazilian Portuguese, involving two distinct local verb-argument combinations (nominal object and pronominal object series). For each volunteer, the EEG was simultaneously acquired at 20 derivations, topographically localized according to the 10-20 International System. A computerized routine for automatic N400-peak marking (based on the ascendant zero-cross of the first waveform derivative) was applied to the estimated individual ERP waveform for congruous and incongruous sentences in both series for all ERP topographic derivations. Peak-to-peak N400 amplitude was significantly augmented (P < 0.05; one-sided Wilcoxon signed-rank test) due to incongruence in derivations F3, T3, C3, Cz, T5, P3, Pz, and P4 for nominal object series and in P3, Pz and P4 for pronominal object series. The results also indicated high inter-individual variability in ERP waveforms, suggesting that the usual procedure of grand averaging might not be considered a generally adequate approach. Hence, signal processing statistical techniques should be applied in neurolinguistic ERP studies allowing waveform analysis with low signal-to-noise ratio.
Resumo:
In the present review, we describe a systematic study of the sulfated polysaccharides from marine invertebrates, which led to the discovery of a carbohydrate-based mechanism of sperm-egg recognition during sea urchin fertilization. We have described unique polymers present in these organisms, especially sulfated fucose-rich compounds found in the egg jelly coat of sea urchins. The polysaccharides have simple, linear structures consisting of repeating units of oligosaccharides. They differ among the various species of sea urchins in specific patterns of sulfation and/or position of the glycosidic linkage within their repeating units. These polysaccharides show species specificity in inducing the acrosome reaction in sea urchin sperm, providing a clear-cut example of a signal transduction event regulated by sulfated polysaccharides. This distinct carbohydrate-mediated mechanism of sperm-egg recognition coexists with the bindin-protein system. Possibly, the genes involved in the biosynthesis of these sulfated fucans did not evolve in concordance with evolutionary distance but underwent a dramatic change near the tip of the Strongylocentrotid tree. Overall, we established a direct causal link between the molecular structure of a sulfated polysaccharide and a cellular physiological event - the induction of the sperm acrosome reaction in sea urchins. Small structural changes modulate an entire system of sperm-egg recognition and species-specific fertilization in sea urchins. We demonstrated that sulfated polysaccharides - in addition to their known function in cell proliferation, development, coagulation, and viral infection - mediate fertilization, and respond to evolutionary mechanisms that lead to species diversity.
Resumo:
It has been shown that mental rotation of objects and human body parts is processed differently in the human brain. But what about body parts belonging to other primates? Does our brain process this information like any other object or does it instead maximize the structural similarities with our homologous body parts? We tried to answer this question by measuring the manual reaction time (MRT) of human participants discriminating the handedness of drawings representing the hands of four anthropoid primates (orangutan, chimpanzee, gorilla, and human). Twenty-four right-handed volunteers (13 males and 11 females) were instructed to judge the handedness of a hand drawing in palm view by pressing a left/right key. The orientation of hand drawings varied from 0º (fingers upwards) to 90º lateral (fingers pointing away from the midline), 180º (fingers downwards) and 90º medial (finger towards the midline). The results showed an effect of rotation angle (F(3, 69) = 19.57, P < 0.001), but not of hand identity, on MRTs. Moreover, for all hand drawings, a medial rotation elicited shorter MRTs than a lateral rotation (960 and 1169 ms, respectively, P < 0.05). This result has been previously observed for drawings of the human hand and related to biomechanical constraints of movement performance. Our findings indicate that anthropoid hands are essentially equivalent stimuli for handedness recognition. Since the task involves mentally simulating the posture and rotation of the hands, we wondered if "mirror neurons" could be involved in establishing the motor equivalence between the stimuli and the participants' own hands.
Resumo:
Facial expressions of basic emotions have been widely used to investigate the neural substrates of emotion processing, but little is known about the exact meaning of subjective changes provoked by perceiving facial expressions. Our assumption was that fearful faces would be related to the processing of potential threats, whereas angry faces would be related to the processing of proximal threats. Experimental studies have suggested that serotonin modulates the brain processes underlying defensive responses to environmental threats, facilitating risk assessment behavior elicited by potential threats and inhibiting fight or flight responses to proximal threats. In order to test these predictions about the relationship between fearful and angry faces and defensive behaviors, we carried out a review of the literature about the effects of pharmacological probes that affect 5-HT-mediated neurotransmission on the perception of emotional faces. The hypothesis that angry faces would be processed as a proximal threat and that, as a consequence, their recognition would be impaired by an increase in 5-HT function was not supported by the results reviewed. In contrast, most of the studies that evaluated the behavioral effects of serotonin challenges showed that increased 5-HT neurotransmission facilitates the recognition of fearful faces, whereas its decrease impairs the same performance. These results agree with the hypothesis that fearful faces are processed as potential threats and that 5-HT enhances this brain processing.
Resumo:
Questions concerning perception are as old as the field of philosophy itself. Using the first-person perspective as a starting point and philosophical documents, the study examines the relationship between knowledge and perception. The problem is that of how one knows what one immediately perceives. The everyday belief that an object of perception is known to be a material object on grounds of perception is demonstrated as unreliable. It is possible that directly perceived sensible particulars are mind-internal images, shapes, sounds, touches, tastes and smells. According to the appearance/reality distinction, the world of perception is the apparent realm, not the real external world. However, the distinction does not necessarily refute the existence of the external world. We have a causal connection with the external world via mind-internal particulars, and therefore we have indirect knowledge about the external world through perceptual experience. The research especially concerns the reasons for George Berkeley’s claim that material things are mind-dependent ideas that really are perceived. The necessity of a perceiver’s own qualities for perceptual experience, such as mind, consciousness, and the brain, supports the causal theory of perception. Finally, it is asked why mind-internal entities are present when perceiving an object. Perception would not directly discern material objects without the presupposition of extra entities located between a perceiver and the external world. Nevertheless, the results show that perception is not sufficient to know what a perceptual object is, and that the existence of appearances is necessary to know that the external world is being perceived. However, the impossibility of matter does not follow from Berkeley’s theory. The main result of the research is that singular knowledge claims about the external world never refer directly and immediately to the objects of the external world. A perceiver’s own qualities affect how perceptual objects appear in a perceptual situation.
Resumo:
Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.
Resumo:
A modified version of the intruder-resident paradigm was used to investigate if social recognition memory lasts at least 24 h. One hundred and forty-six adult male Wistar rats were used. Independent groups of rats were exposed to an intruder for 0.083, 0.5, 2, 24, or 168 h and tested 24 h after the first encounter with the familiar or a different conspecific. Factor analysis was employed to identify associations between behaviors and treatments. Resident rats exhibited a 24-h social recognition memory, as indicated by a 3- to 5-fold decrease in social behaviors in the second encounter with the same conspecific compared to those observed for a different conspecific, when the duration of the first encounter was 2 h or longer. It was possible to distinguish between two different categories of social behaviors and their expression depended on the duration of the first encounter. Sniffing the anogenital area (49.9% of the social behaviors), sniffing the body (17.9%), sniffing the head (3%), and following the conspecific (3.1%), exhibited mostly by resident rats, characterized social investigation and revealed long-term social recognition memory. However, dominance (23.8%) and mild aggression (2.3%), exhibited by both resident and intruders, characterized social agonistic behaviors and were not affected by memory. Differently, sniffing the environment (76.8% of the non-social behaviors) and rearing (14.3%), both exhibited mostly by adult intruder rats, characterized non-social behaviors. Together, these results show that social recognition memory in rats may last at least 24 h after a 2-h or longer exposure to the conspecific.
Resumo:
Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.
Resumo:
Metal-ion-mediated base-pairing of nucleic acids has attracted considerable attention during the past decade, since it offers means to expand the genetic code by artificial base-pairs, to create predesigned molecular architecture by metal-ion-mediated inter- or intra-strand cross-links, or to convert double stranded DNA to a nano-scale wire. Such applications largely depend on the presence of a modified nucleobase in both strands engaged in the duplex formation. Hybridization of metal-ion-binding oligonucleotide analogs with natural nucleic acid sequences has received much less attention in spite of obvious applications. While the natural oligonucleotides hybridize with high selectivity, their affinity for complementary sequences is inadequate for a number of applications. In the case of DNA, for example, more than 10 consecutive Watson-Crick base pairs are required for a stable duplex at room temperature, making targeting of sequences shorter than this challenging. For example, many types of cancer exhibit distinctive profiles of oncogenic miRNA, the diagnostics of which is, however, difficult owing to the presence of only short single stranded loop structures. Metallo-oligonucleotides, with their superior affinity towards their natural complements, would offer a way to overcome the low stability of short duplexes. In this study a number of metal-ion-binding surrogate nucleosides were prepared and their interaction with nucleoside 5´-monophosphates (NMPs) has been investigated by 1H NMR spectroscopy. To find metal ion complexes that could discriminate between natural nucleobases upon double helix formation, glycol nucleic acid (GNA) sequences carrying a PdII ion with vacant coordination sites at a predetermined position were synthesized and their affinity to complementary as well as mismatched counterparts quantified by UV-melting measurements.
Resumo:
Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.
Resumo:
One group of 12 non learning disabled students and two groups of 12 learning disabled students between the ges of 10 and 12 were measured on implicit and explicit knowledge cquisition. Students in each group implicitly cquired knowledge bout I of 2 vocabulary rules. The vocabulary rules governed the pronunciation of 2 types of pseudowords. After completing the implicit acquisition phase, all groups were administered a test of implicit knowledge. The non learning disabled group and I learning disabled group were then asked to verbalize the knowledge acquired during the initial phase. This was a test of explicit knowledge. All 3 groups were then given a postlest of implicit knowledge. This tcst was a measure of the effectiveness of the employment of the verbalization technique. Results indicate that implicit knowledge capabilities for both the learning disabled and non learning disabled groups were intact. However. there were significant differences between groups on explicit knowledge capabilities. This led to the conclusion that implicit functions show little individual differences, and that explicit functions are affected by ability difference. Furthermore, the employment of the verbalization technique significantly increased POStlest scores for learning disabled students. This suggested that the use of metacognitive techniques was a beneficial learning tool for learning disabled students.
Resumo:
The perovskite crystal structure is host to many different materials from insulating to superconducting providing a diverse range of intrinsic character and complexity. A better fundamental description of these materials in terms of their electronic, optical and magnetic properties undoubtedly precedes an effective realization of their application potential. SmTiOa, a distorted perovskite has a strongly localized electronic structure and undergoes an antiferromagnetic transition at 50 K in its nominally stoichiometric form. Sr2Ru04 is a layered perovskite superconductor (ie. Tc % 1 K) bearing the same structure as the high-tem|>erature superconductor La2_xSrrCu04. Polarized reflectance measurements were carried out on both of these materials revealing several interesting features in the far-infrared range of the spectrum. In the case of SmTiOa, although insulating, evidence indicates the presence of a finite background optical conductivity. As the temperature is lowered through the ordering temperature a resonance feature appears to narrow and strengthen near 120 cm~^ A nearby phonon mode appears to also couple to this magnetic transition as revealed by a growing asymmetry in the optica] conductivity. Experiments on a doped sample with a greater itinerant character and lower Neel temperature = 40 K also indicate the presence of this strongly temperature dependent mode even at twice the ordering temperature. Although the mode appears to be sensitive to the magnetic transition it is unclear whether a magnon assignment is appropriate. At very least, evidence suggests an interesting interaction between magnetic and electronic excitations. Although Sr2Ru04 is highly anisotropic it is metallic in three-dimensions at low temperatures and reveals its coherent transport in an inter-plane Drude-like component to the highest temperatures measured (ie. 90 K). An extended Drude analysis is used to probe the frequency dependent scattering character revealing a peak in both the mass enhancement and scattering rate near 80 cm~* and 100 cm~* respectively. All of these experimental observations appear relatively consistent with a Fermi-liquid picture of charge transport. To supplement the optical measurements a resistivity station was set up with an event driven object oriented user interface. The program controls a Keithley Current Source, HP Nano-Voltmeter and Switching Unit as well as a LakeShore Temperature Controller in order to obtain a plot of the Resistivity as a function of temperature. The system allows for resistivity measurements ranging from 4 K to 290 K using an external probe or between 0.4 K to 295 K using a Helium - 3 Cryostat. Several materials of known resistivity have confirmed the system to be robust and capable of measuring metallic samples distinguishing features of several fiQ-cm.
Resumo:
Adults' expert face recognition is limited to the kinds of faces they encounter on a daily basis (typically upright human faces of the same race). Adults process own-race faces holistically (Le., as a gestalt) and are exquisitely sensitive to small differences among faces in the spacing of features, the shape of individual features and the outline or contour of the face (Maurer, Le Grand, & Mondloch, 2002), however this expertise does not seem to extend to faces from other races. The goal of the current study was to investigate the extent to which the mechanisms that underlie expert face processing of own-race faces extend to other-race faces. Participants from rural Pennsylvania that had minimal exposure to other-race faces were tested on a battery of tasks. They were tested on a memory task, two measures of holistic processing (the composite task and the part/whole task), two measures of spatial and featural processing (the JanelLing task and the scrambledlblurred faces task) and a test of contour processing (JanelLing task) for both own-and other-race faces. No study to date has tested the same participants on all of these tasks. Participants had minimal experience with other-race faces; they had no Chinese family members, friends or had ever traveled to an Asian country. Results from the memory task did not reveal an other-race effect. In the present study, participants also demonstrated holistic processing of both own- and other-race faces on both the composite task and the part/whole task. These findings contradict previous findings that Caucasian adults process own-race faces more holistically than other-race faces. However participants did demonstrate an own-race advantage for processing the spacing among features, consistent with two recent studies that used different manipulations of spacing cues (Hayward et al. 2007; Rhodes et al. 2006). They also demonstrated an other-race effect for the processing of individual features for the Jane/Ling task (a direct measure of featural processing) consistent with previous findings (Rhodes, Hayward, & Winkler, 2006), but not for the scrambled faces task (an indirect measure offeatural processing). There was no own-race advantage for contour processing. Thus, these results lead to the conclusion that individuals may show less sensitivity to the appearance of individual features and the spacing among them in other-race faces, despite processing other-race faces holistically.