951 resultados para visual representation


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Starting with the incident now known as the Cow’s Head Protest, this article traces and unpacks the events, techniques, and conditions surrounding the representation of ethno-religious minorities in Malaysia. The author suggests that the Malaysian Indians’ struggle to correct the dominant reading of their community as an impoverished and humbled underclass is a disruption of the dominant cultural order in Malaysia. It is also among the key events to have has set in motion a set of dynamics—the visual turn—introduced by new media into the politics of ethno-communal representation in Malaysia. Believing that this situation requires urgent examination the author attempts to outline the problematics of the task.

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This article provides a tutorial introduction to visual servo control of robotic manipulators. Since the topic spans many disciplines our goal is limited to providing a basic conceptual framework. We begin by reviewing the prerequisite topics from robotics and computer vision, including a brief review of coordinate transformations, velocity representation, and a description of the geometric aspects of the image formation process. We then present a taxonomy of visual servo control systems. The two major classes of systems, position-based and image-based systems, are then discussed in detail. Since any visual servo system must be capable of tracking image features in a sequence of images, we also include an overview of feature-based and correlation-based methods for tracking. We conclude the tutorial with a number of observations on the current directions of the research field of visual servo control.

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Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

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We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.

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The present study investigated how object locations learned separately are integrated and represented as a single spatial layout in memory. Two experiments were conducted in which participants learned a room-sized spatial layout that was divided into two sets of five objects. Results suggested that integration across sets was performed efficiently when it was done during initial encoding of the environment but entailed cost in accuracy when it was attempted at the time of memory retrieval. These findings suggest that, once formed, spatial representations in memory generally remain independent and integrating them into a single representation requires additional cognitive processes.

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This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

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Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In previous work we introduced a method to update the reference views in a topological map so that a mobile robot could continue to localize itself in a changing environment using omni-directional vision. In this work we extend this longterm updating mechanism to incorporate a spherical metric representation of the observed visual features for each node in the topological map. Using multi-view geometry we are then able to estimate the heading of the robot, in order to enable navigation between the nodes of the map, and to simultaneously adapt the spherical view representation in response to environmental changes. The results demonstrate the persistent performance of the proposed system in a long-term experiment.

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Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.

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Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

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Representation of Aborigines by Aborigines and non -Aborigines; articles by Andrew Dewdney, Mervyn Biship, Alana Harris, Sandy Edwards, Rea Saunders, Ricky Maynard , Brenda Croft, Ruth Braunstein, Michael Riley, Huw Davies, Penny Taylor, Darlene McKenzie, Kurt Brereton and Eric Michaels, annotated separately.

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Previous neuroimaging research has attempted to demonstrate a preferential involvement of the human mirror neuron system (MNS) in the comprehension of effector-related action word (verb) meanings. These studies have assumed that Broca's area (or Brodmann's area 44) is the homologue of a monkey premotor area (F5) containing mouth and hand mirror neurons, and that action word meanings are shared with the mirror system due to a proposed link between speech and gestural communication. In an fMRI experiment, we investigated whether Broca's area shows mirror activity solely for effectors implicated in the MNS. Next, we examined the responses of empirically determined mirror areas during a language perception task comprising effector-specific action words, unrelated words and nonwords. We found overlapping activity for observation and execution of actions with all effectors studied, i.e., including the foot, despite there being no evidence of foot mirror neurons in the monkey or human brain. These "mirror" areas showed equivalent responses for action words, unrelated words and nonwords, with all of these stimuli showing increased responses relative to visual character strings. Our results support alternative explanations attributing mirror activity in Broca's area to covert verbalisation or hierarchical linearisation, and provide no evidence that the MNS makes a preferential contribution to comprehending action word meanings.

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Spoken term detection (STD) is the task of looking up a spoken term in a large volume of speech segments. In order to provide fast search, speech segments are first indexed into an intermediate representation using speech recognition engines which provide multiple hypotheses for each speech segment. Approximate matching techniques are usually applied at the search stage to compensate the poor performance of automatic speech recognition engines during indexing. Recently, using visual information in addition to audio information has been shown to improve phone recognition performance, particularly in noisy environments. In this paper, we will make use of visual information in the form of lip movements of the speaker in indexing stage and will investigate its effect on STD performance. Particularly, we will investigate if gains in phone recognition accuracy will carry through the approximate matching stage to provide similar gains in the final audio-visual STD system over a traditional audio only approach. We will also investigate the effect of using visual information on STD performance in different noise environments.

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The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.

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Tourism is one of important livelihoods in Lapland. Christmas tourism was launched in the early 1980s and it became a success story - being labelled as the most epochal tourism product in Finland. Hence, today Christmas tourists are one of the most significant foreign groups arriving to Lapland during the winter season and contributing considerably to the economics of the northeastern periphery of the EU. Christmas tourism concentrates around Father Christmas who uses reindeer for transportation. The Sämi are the only indigenous people in the EU. They are all stereotypically perceived to be reindeer herders. Somehow these three, that is, Santa Claus, reindeer and the Sämi, have been incorporated into same fairytale dominion. In practice, this has happened by using the most visible cultural but also significant identity marker of the Sämi, the Sämi costume. This, in turn, has created controversy over authenticity due to manners in which the costume is used in tourism - often in imitational, mismatched forms by non-Sämi. In this thesis, after relevant literature review I intend to establish how the Sâmi are represented in Christmas tourism through visual data consisting of ten images from three foreign sources. Then I clarify why and to whom it matters of how the Sâmi are represented in Christmas tourism with the aid of 65 questionnaires and nineteen expert interviews collected mainly in the Finnish Sâmi Home Region in October 2009. Through the multiplicity of the voices of various interest and ethnic groups and by using critical discourse analysis I attempt to give an overview of the respondents' opinions and look at some preliminary solutions to the controversy. Based on my data, the non-Sami appear to accept the Sami costume usage in Christmas tourism most readily. Consequently, respect and attitudinal changes have become the respondents' propositions in addition to common set of rules of how the Sami image could be appropriated without violating the integrity of the Sami people, or a similar system of S¿m¡ Duodji trademark guaranteeing the authenticity of the tourism products. Additionally, though half of the interviewees explicate Sami presence in Christmas tourism by adding local flavour to otherwise commercial enterprise, the other half see no rationale to connect facts with fiction, that is, the Sami with Santa Claus.

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Tourism is one of important livelihoods in Lapland. Christmas tourism was launched in the early 1980s and it became a success story - being labelled as the most epochal tourism product in Finland. Hence, today Christmas tourists are one of the most significant foreign groups arriving to Lapland during the winter season and contributing considerably to the economics of the northeastern periphery of the EU. Christmas tourism concentrates around Father Christmas who uses reindeer for transportation. The Sämi are the only indigenous people in the EU. They are all stereotypically perceived to be reindeer herders. Somehow these three, that is, Santa Claus, reindeer and the Sämi, have been incorporated into same fairytale dominion. In practice, this has happened by using the most visible cultural but also significant identity marker of the Sämi, the Sämi costume. This, in turn, has created controversy over authenticity due to manners in which the costume is used in tourism - often in imitational, mismatched forms by non-Sämi. In this thesis, after relevant literature review I intend to establish how the Sâmi are represented in Christmas tourism through visual data consisting of ten images from three foreign sources. Then I clarify why and to whom it matters of how the Sâmi are represented in Christmas tourism with the aid of 65 questionnaires and nineteen expert interviews collected mainly in the Finnish Sâmi Home Region in October 2009. Through the multiplicity of the voices of various interest and ethnic groups and by using critical discourse analysis I attempt to give an overview of the respondents' opinions and look at some preliminary solutions to the controversy. Based on my data, the non-Sami appear to accept the Sami costume usage in Christmas tourism most readily. Consequently, respect and attitudinal changes have become the respondents' propositions in addition to common set of rules of how the Sami image could be appropriated without violating the integrity of the Sami people, or a similar system of S¿m¡ Duodji trademark guaranteeing the authenticity of the tourism products. Additionally, though half of the interviewees explicate Sami presence in Christmas tourism by adding local flavour to otherwise commercial enterprise, the other half see no rationale to connect facts with fiction, that is, the Sami with Santa Claus.