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ispartof: PSYCHOLOGY OF AESTHETICS CREATIVITY AND THE ARTS vol:17 issue:3 status: Published online

Luego de muchos años de conflicto armado en Colombia, acordaron y firmaron un Acuerdo Final para la terminación del conflicto y la construcción de la paz, pues se ha desarrollado una característica fundamental dentro de este acuerdo que se basa en la reincorporación de los excombatientes para transformarlos en ciudadanos con plenos derechos y obligaciones. Cabe destacar que en todo proceso de reincorporación las garantías de seguridad se comportan como un factor altamente importante para lograr el éxito y prevenir la reincidencia. Por tanto, se menciona la acción institucional como garante de los derechos de los ciudadanos a través del cumplimiento del acuerdo para encaminarse a satisfacer las medidas de protección y autoprotección, ya que las cifras de agresiones ponen en evidencia las limitaciones del modelo actual. El propósito de este ensayo surge del interés de analizar las diferentes barreras con las que se enfrentan las empresas de seguridad privada para brindar empleos dignos en a los reincorporados de la guerrilla de las FARC. En base a consultas, análisis, indagatorias, noticias, artículos de opinión, y teniendo en cuenta algunas actividades que venían realizando los miembros este grupo al margen de la ley, se presume que las empresas de seguridad privada son una posible fuente generadora de empleos para los reincorporados. De igual manera, es importante conocer los riesgos asociados que trae consigo un proceso como este, traer a la vida civil desmovilizados sin el acompañamiento de un plan social, en donde no solo se involucre al estado con las soluciones de empleo, educación, vivienda y salud; se debe tener en cuenta que gran parte de esas fuentes de empleo están en las empresas privadas, en este caso particular, las empresas de vigilancia y seguridad privada. Es necesaria, la adopción de medidas y compromisos serios especialmente en lo relacionado con la seguridad física de los desmovilizados. El proceso de reincorporación a la vida civil es un tema bastante sonado en los últimos tiempos en el país, se conoce el tema a través de lo publicado por las noticias locales, medios de comunicación que investigan el tema, publicaciones en las revistas más influyentes de país, entre otros. Pero realmente que significa para los colombianos escuchar este término con más frecuencia. Partiendo de una frase bastante diciente y que va de la mano del tema principal de este escrito “La reinserción es la clave de la paz en Colombia”. Estas palabras desde ciertos puntos de vista son la solución a la guerra que agobia al país desde hace muchos años, pero también se puede convertir en una falsa esperanza con la que sueñas los colombianos a diario. Colombia vive uno de los momentos más cruciales, en relación a inclusión de estas personas a la vida civil, uno de los trabajos más atractivos para los reincorporados son los asociados a la vigilancia y seguridad privada; esto muy probablemente ligado a el oficio que desempeñaban en los campos donde operaban anteriormente. La vigilancia como empleo, les representa la oportunidad de reintegrarse activamente a la sociedad civil, lo cual cumple un rol realmente importante para que la paz se construya de manera idónea en la población colombiana. Y es aquí donde surge un gran y complejo interrogante, ¿Cuáles son las diferentes barreras con las que se enfrentan las empresas de seguridad privada para brindar empleos dignos en a los reincorporados de la guerrilla de las FARC? After many years of armed conflict in Colombia, they agreed and signed a Final Agreement for the termination of the conflict and the construction of peace, since a fundamental feature has been developed within this agreement that is based on the reincorporation of ex-combatants to transform them in citizens with full rights and obligations. It should be noted that in any reincorporation process, security guarantees behave as a highly important factor to achieve success and prevent recidivism. Therefore, institutional action is mentioned as a guarantor of citizens' rights through compliance with the agreement in order to satisfy protection and self-protection measures, since the numbers of aggressions highlight the limitations of the current model. The purpose of this essay arises from the interest of analyzing the different barriers that private security companies face to provide decent jobs to the FARC's reincorporated guerrillas. Based on consultations, analyzes, inquiries, news, opinion articles, and taking into account some activities that members of this group had been doing outside the law, it is presumed that private security companies are a possible source of employment for the reincorporated. In the same way, it is important to know the associated risks that a process like this brings, bringing demobilized people to civil life without the accompaniment of a social plan, where the state is not only involved with employment, education, housing and Health; It should be taken into account that a large part of these sources of employment are in private companies, in this particular case, private security and surveillance companies. It is necessary, the adoption of measures and serious commitments especially in relation to the physical security of the demobilized. The process of reincorporation into civilian life is a fairly well-known topic in recent times in the country, the topic is known through what has been published by local news, the media investigating the issue, publications in the most influential magazines in country, among others. But it really means for Colombians to hear this term more frequently. Starting from a fairly telling phrase that goes hand in hand with the main theme of this writing "Reintegration is the key to peace in Colombia." These words from certain points of view are the solution to the war that has plagued the country for many years, but it can also become a false hope that Colombians dream about on a daily basis. Colombia is experiencing one of the most crucial moments, in relation to the inclusion of these people in civilian life. One of the most attractive jobs for the reinstated is those associated with private security and surveillance; This is most likely linked to the trade they held in the fields where they previously operated. Surveillance as a job represents the opportunity to actively reintegrate into civil society, which plays a really important role so that peace is built in an ideal way in the Colombian population. And this is where a big and complex question arises, what are the different barriers that private security companies face to provide decent jobs to the FARC guerrilla reincorporated? Especialización

The early visual system is composed of spatial frequency-tuned channels that break an image into its individual frequency components. Therefore, researchers commonly filter images for spatial frequencies to arrive at conclusions about the differential importance of high versus and low spatial frequency image content. Here, we show how simple decisions about the filtering of the images, and how they are displayed on the screen, can result in drastically different behavioral outcomes. We show that jointly normalizing the contrast of the stimuli is critical in order to draw accurate conclusions about the influence of the different spatial frequencies, as images of the real world naturally have higher contrast energy at low than high spatial frequencies. Furthermore, the specific choice of filter shape can result in contradictory results about whether high or low spatial frequencies are more useful for understanding image content. Finally, we show that the manner in which the high spatial frequency content is displayed on the screen influences how recognizable an image is. Previous findings that make claims about the visual system&rsquo, s use of certain spatial frequency bands should be revisited, especially if their methods sections do not make clear what filtering choices were made.

We often take people’s ability to understand and produce line drawings for granted. But where should we draw lines, and why? We address fundamental principles that underlie efficient representations of complex information in line drawings. First, 58 participants with varying degree of artistic experience produced multiple drawings of a small set of scenes by tracing contours on a digital tablet. Second, 37 independent observers ranked the drawings by how representative they are of the original photograph. Overall, artists’ drawings ranked higher than non-artists’. Matching contours between drawings of the same scene revealed that the most consistently drawn contours tend to be drawn earlier. We generated half-images with the most-versus least-consistently drawn contours by sorting contours by their consistency scores. Twenty five observers performed significantly better in a fast scene categorization task for the most compared to the least consistent half-images. The most consistent contours were longer and more likely to depict occlusion boundaries. Using psychophysics experiments and computational analysis, we confirmed quantitatively what makes certain contours in line drawings special: longer contours mark occlusion boundaries and aid rapid scene recognition. They allow artist and non-artists to convey important information starting from the first few strokes in their drawing process.

People are able to perceive the 3D shape of illuminated surfaces using image shading cues. Theories about how we accomplish this often assume that the human visual system estimates a single lighting direction and interprets shading cues in accord with that estimate. In natural scenes, however, lighting can be much more complex than this, with multiple nearby light sources. Here we show that the human visual system can successfully judge 3D surface shape even when the lighting direction varies from place to place over a surface, provided the scale at which these lighting changes occur is similar to, or larger than, the size of the shape features being judged. Furthermore, we show that despite being able to accommodate rapid changes in lighting direction when judging shape, observers are generally unable to detect these changes. We conclude that, rather than relying on a single estimated illumination direction, the human visual system can accommodate illumination that varies substantially and rapidly across a surface.

The computer vision community has witnessed recent advances in scene categorization from images, with the state-of-the art systems now achieving impressive recognition rates on challenging benchmarks such as the Places365 dataset. Such systems have been trained on photographs which include color, texture and shading cues. The geometry of shapes and surfaces, as conveyed by scene contours, is not explicitly considered for this task. Remarkably, humans can accurately recognize natural scenes from line drawings, which consist solely of contour-based shape cues. Here we report the first computer vision study on scene categorization of line drawings derived from popular databases including an artist scene database, MIT67, and Places365. Specifically, we use off-the-shelf pre-trained CNNs to perform scene classification given only contour information as input and find performance levels well above chance. We also show that medial-axis based contour salience methods can be used to select more informative subsets of contour pixels and that the variation in CNN classification performance on various choices for these subsets is qualitatively similar to that observed in human performance. Moreover, when the salience measures are used to weight the contours, as opposed to pruning them, we find that these weights boost our CNN performance above that for unweighted contour input. That is, the medial axis based salience weights appear to add useful information that is not available when CNNs are trained to use contours alone.

Photographs and line drawings of natural scenes are easily classified even when the image is only briefly visible to the observer. Contour junctions and points of high curvature have been shown to be important for perceptual organization (Attneave, 1954; Biederman, 1987) and have been proposed to be influential in rapid scene classification (Walther & Shen, 2014). Here, we manipulate the junctions in images, either randomly translating them, or selectively removing or maintaining them. Observers were better at classifying images when the contours were randomly translated (disrupting the junctions) than when the junctions were randomly shifted (partially disrupting contour information). Moreover, observers were better at classifying a scene when shown only segments between junctions, than when shown only the junctions, with the middle segments removed. These results suggest that categorizing line drawings of real-world scenes does not solely rely on junction statistics. The spatial locations of the junctions are important, as well as their relationships with one another. Furthermore, the segments between junctions appear to facilitate scene classification, possibly due to their involvement in symmetry relationships with other contour segments.

People are able to rapidly categorize briefly flashed images of real-world environments, even when they are reduced to line drawings. This setting allows for the study of time-limited perceptual grouping processes in the human visual system that are applicable to line drawings. Previous work (Wilder, Dickinson, Jepson, & Walther, 2018) showed that standard local features of individual contours, or junctions between contours, do not account for this rapid classification ability but, rather, the relative placement of these contours appeared to be important. Here we provide strong support for this observation by demonstrating that local ribbon symmetry between neighboring pairs of contours facilitates the categorization of complex real-world environments. To this end, we introduce a novel computational approach, based on the medial axis transform, for measuring the degree of local ribbon symmetry in a line drawing. We use this measure to separate the contour pixels for a given scene into the most ribbon symmetric half and the least ribbon symmetric half. We then show human observers the resulting half-images in a rapid-categorization experiment. Our results demonstrate that local ribbon symmetry facilitates the categorization of complex real-world environments. This is the first study of the role of local symmetry in inter-contour grouping for human scene classification. We conclude that local ribbon symmetry appears to play an important role in jump-starting the grouping of image content into meaningful units, even in flashed presentations.

This paper investigates the classification of shapes into broad natural categories such as animal or leaf. We asked whether such coarse classifications can be achieved by a simple statistical classification of the shape skeleton. We surveyed databases of natural shapes, extracting shape skeletons and tabulating their parameters within each class, seeking shape statistics that effectively discriminated the classes. We conducted two experiments in which human subjects were asked to classify novel shapes into the same natural classes. We compared subjects’ classifications to those of a naive Bayesian classifier based on the natural shape statistics, and found good agreement. We conclude that human superordinate shape classifications can be well understood as involving a simple statistical classification of the shape skeleton that has been “tuned” to the natural statistics of shape.

Classification image analysis is a powerful technique for elucidating linear detection and discrimination mechanisms, but it has primarily been applied to contrast detection. Here we report a novel classification image methodology for identifying linear mechanisms underlying shape discrimination. Although prior attempts to apply classification image methods to shape perception have been confined to simple radial shapes, the method proposed here can be applied to general 2-D (planar) shapes of arbitrary complexity, including natural shapes. Critical to the method is the projection of each target shape onto a Fourier descriptor (FD) basis set, which allows the essential perceptual features of each shape to be represented by a relatively small number of coefficients. We demonstrate that under this projection natural shapes are low pass, following a relatively steep power law. To efficiently identify the observer's classification template, we employ a yes/no paradigm and match the spectral density of the stimulus noise in FD space to the power law density of the target shape. The proposed method generates linear template models for animal shape detection that are predictive of human judgments. These templates are found to be biased away from the ideal, overly weighting lower frequencies. This low-pass bias suggests that higher frequency shape processing relies on nonlinear mechanisms.

Visual attention and saccades are typically studied in artificial situations, with stimuli presented to the steadily fixating eye, or saccades made along specified paths. By contrast, in real-world tasks saccadic patterns are constrained only by the demands of the motivating task. We studied attention during pauses between saccades made to perform three free-viewing tasks: counting dots, pointing to the same dots with a visible cursor, or simply looking at the dots using a freely-chosen path. Attention was assessed by the ability to identify the orientation of a briefly-presented Gabor probe. All primary tasks produced losses in identification performance, with counting producing the largest losses, followed by pointing and then looking-only. Looking-only resulted in a 37% increase in contrast thresholds in the orientation task. Counting produced more severe losses that were not overcome by increasing Gabor contrast. Detection or localization of the Gabor, unlike identification, were largely unaffected by any of the primary tasks. Taken together, these results show that attention is required to control saccades, even with freely-chosen paths, but the attentional demands of saccades are less than those attached to tasks such as counting, which have a significant cognitive load. Counting proved to be a highly demanding task that either exhausted momentary processing capacity (e.g., working memory or executive functions), or, alternatively, encouraged a strategy of filtering out all signals irrelevant to counting itself. The fact that the attentional demands of saccades (as well as those of detection/localization) are relatively modest makes it possible to continually adjust both the spatial and temporal pattern of saccades so as to re-allocate attentional resources as needed to handle the complex and multifaceted demands of real-world environments.

The detection of contours in noise has been extensively studied, but the detection of closed contours, such as the boundaries of whole objects, has received relatively little attention. Closed contours pose substantial challenges not present in the simple (open) case, because they form the outlines of whole shapes and thus take on a range of potentially important configural properties. In this paper we consider the detection of closed contours in noise as a probabilistic decision problem. Previous work on open contours suggests that contour complexity, quantified as the negative log probability (Description Length, DL) of the contour under a suitably chosen statistical model, impairs contour detectability; more complex (statistically surprising) contours are harder to detect. In this study we extended this result to closed contours, developing a suitable probabilistic model of whole shapes that gives rise to several distinct though interrelated measures of shape complexity. We asked subjects to detect either natural shapes (Exp. 1) or experimentally manipulated shapes (Exp. 2) embedded in noise fields. We found systematic effects of global shape complexity on detection performance, demonstrating how aspects of global shape and form influence the basic process of object detection.

We present a unified Bayesian approach to shape representation and related problems in perceptual organization, including part decomposition, shape similarity, figure/ground estimation, and 3D shape. The approach is based on the idea of estimating the skeletal structure most likely to have generated the observed shape via a process of stochastic “growth.” We survey the approach briefly and show how it can be extended in a principled way to solve a wide array of related problems.

It is well-known that “smooth” chains of oriented elements—contours—are more easily detected amid background noise than more undulating (i.e., “less smooth”) chains. Here, we develop a Bayesian framework for contour detection and show that it predicts that contour detection performance should decrease with the contour's complexity, quantified as the description length (DL; i.e., the negative logarithm of probability integrated along the contour). We tested this prediction in two experiments in which subjects were asked to detect simple open contours amid pixel noise. In Experiment 1, we demonstrate a consistent decline in performance with increasingly complex contours, as predicted by the Bayesian model. In Experiment 2, we confirmed that this effect is due to integrated complexity along the contour, and does not seem to depend on local stretches of linear structure. The results corroborate the probabilistic model of contours, and show how contour detection can be understood as a special case of a more general process—the identification of organized patterns in the environment.