This article deals with automatic object recognition. The goal is that in a certain grey-level image, possibly containing many objects, a certain object can be recognized and localized, based upon its shape. The assumption is that this shape has no special characteristics on which a dedicated recognition algorithm can be based (e.g. if we know that the object is circular, we could use a Hough transform or if we know that it is the only object with grey level 90, we can simply use thresholding). Our starting point is an object with a random shape. The image in which the object is searched is called the Search Image. A well known technique for this is Template Matching, which is described first.
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This paper describes the work that is done by a group of I3 students at Philips CFT in Eindhoven, Netherlands. I3 is an initiative of Fontys University of Professional Education also located in Eindhoven. The work focuses on the use of computer vision in motion control. Experiments are done with several techniques for object recognition and tracking, and with the guidance of a robot movement by means of computer vision. These experiments involve detection of coloured objects, object detection based on specific features, template matching with automatically generated templates, and interaction of a robot with a physical object that is viewed by a camera mounted on the robot.
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We will demonstrate a prototype exergame aimed at the serious domain of elderly fitness. The exergame incorporates straightforward means to gesture recognition, and utilises a Kinect camera to obtain 2.5D sensory data of the human user.
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Over the past few years a growing number of artists have critiqued the ubiquity of identity recognition technologies. Specifically, the use of these technologies by state security programs, tech-giants and multinational corporations has met with opposition and controversy. A popular form of resistance to recognition technology is sought in strategies of masking and camouflage. Zach Blas, Leo Selvaggio, Sterling Crispin and Adam Harvey are among a group of internationally acclaimed artists who have developed subversive anti-facial recognition masks that disrupt identification technologies. This paper examines the ontological underpinnings of these popular and widely exhibited mask projects. Over and against a binary understanding and criticism of identity recognition technology, I propose to take a relational turn to reimagine these technologies not as an object for our eyes, but as a relationship between living organisms and things. A relational perspective cuts through dualist and anthropocentric conceptions of recognition technology opening pathways to intersectional forms of resistance and critique. Moreover, if human-machine relationships are to be understood as coming into being in mutual dependency, if the boundaries between online and offline are always already blurred, if the human and the machine live intertwined lives and it is no longer clear where the one stops and the other starts, we need to revise our understanding of the self. A relational understanding of recognition technology moves away from a notion of the self as an isolated and demarcated entity in favour of an understanding of the self as relationally connected, embedded and interdependent. This could alter the way we relate to machines and multiplies the lines of flight we can take out of a culture of calculated settings.
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Maritime Spatial Planning (MSP) is a politically guided and stakeholder-driven process involving a range of actors (i.e., planners, stakeholders, scientists, and citizens). Theories of boundary objects offer a lens to understand how actors, in the context of decision and policy-making in organizations, can coordinate without consensus. This seems particularly relevant when institutions and communities are relatively young, and the body of knowledge is fragmented and fluid, such as in the case of MSP. A key question is whether, and how boundary objects can be intentionally designed and used to facilitate social and policy learning in such communities. In this research, the focus is on the use of the MSP Challenge serious games as a boundary object to facilitate learning in ‘Communities of Practice’ (CoP) around MSP. Data were collected through questionnaires of 62 MSP Challenge workshops between 2016 and 2020 with more than 1100 participants. Additionally, 33 interviews with key stakeholders were conducted. The findings show that the MSP Challenge is widely used for various goals and in various settings and that they are interpreted differently by different users. The success of the MSP Challenge relies on the boundary space in which it is implemented, taking into account discrepancies in learning due to variations in the backgrounds and attitudes of the participants towards the object, the activity, and the setting in which it is deployed.
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Digital surveillance technologies using artificial intelligence (AI) tools such as computer vision and facial recognition are becoming cheaper and easier to integrate into governance practices worldwide. Morocco serves as an example of how such technologies are becoming key tools of governance in authoritarian contexts. Based on qualitative fieldwork including semi-structured interviews, observation, and extensive desk reviews, this chapter focusses on the role played by AI-enhanced technology in urban surveillance and the control of migration between the Moroccan–Spanish borders. Two cross-cutting issues emerge: first, while international donors provide funding for urban and border surveillance projects, their role in enforcing transparency mechanisms in their implementation remains limited; second, Morocco’s existing legal framework hinders any kind of public oversight. Video surveillance is treated as the sole prerogative of the security apparatus, and so far public actors have avoided to engage directly with the topic. The lack of institutional oversight and public debate on the matter raise serious concerns on the extent to which the deployment of such technologies affects citizens’ rights. AI-enhanced surveillance is thus an intrinsically transnational challenge in which private interests of economic gain and public interests of national security collide with citizens’ human rights across the Global North/Global South divide.
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This article focuses on the recent judgment of the Court of Justice, Aranyosi and Caldararu. After conducting a legal analysis on this case, three issues are identified and they are separately discussed in three sections. The aim of this paper is to show the impact of this judgment on public order and public security in Europe on the one hand and on the individual’s fundamental rights, on the other hand. It is going to be argued that even though there are limits to the principle of mutual recognition, this new exception based on fundamental rights establishes a new procedure for non-surrender. Therefore, the Court of Justice creates a non-execution ground which the EU legislator did not intend to include in the Framework Decision on the European arrest warrant. This is explained by looking at the three interconnected notions of Freedom, Security and Justice.
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Objective: To automatically recognize self-acknowledged limitations in clinical research publications to support efforts in improving research transparency.Methods: To develop our recognition methods, we used a set of 8431 sentences from 1197 PubMed Central articles. A subset of these sentences was manually annotated for training/testing, and inter-annotator agreement was calculated. We cast the recognition problem as a binary classification task, in which we determine whether a given sentence from a publication discusses self-acknowledged limitations or not. We experimented with three methods: a rule-based approach based on document structure, supervised machine learning, and a semi-supervised method that uses self-training to expand the training set in order to improve classification performance. The machine learning algorithms used were logistic regression (LR) and support vector machines (SVM).Results: Annotators had good agreement in labeling limitation sentences (Krippendorff's α = 0.781). Of the three methods used, the rule-based method yielded the best performance with 91.5% accuracy (95% CI [90.1-92.9]), while self-training with SVM led to a small improvement over fully supervised learning (89.9%, 95% CI [88.4-91.4] vs 89.6%, 95% CI [88.1-91.1]).Conclusions: The approach presented can be incorporated into the workflows of stakeholders focusing on research transparency to improve reporting of limitations in clinical studies.
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An array of studies has shown that games can be suitable for marketing communication - but that not all game genres can be expected to be equally successful in generating advertising effects. Since the game task in shooter games requests players to strictly focus on objects that can pose a threat, that game genre seems especially problematic for in-game advertising. Subliminal communication can theoretically be expected to overcome (part) of that problem. Therefore, our experimental study (N = 143) focuses on marketing communication effects of subliminally presented brand logos. We aim to find out (i) whether subliminal marketing communication causes recognition effects and (ii) whether pictorial logos differ from textual logos in the size of the effect they generate. This way we can shine a light on the message processing mechanisms that are foundational to subliminal message effects. The results of our study show that subliminally presented brand logos do have a communicative potential: the recognition effects are significant. Besides, our study indicates that pictorial logos have a greater propensity to subliminally communicate than textual logos.
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From the introduction: "There are two variants of fronto-temporal dementia: a behavioral variant (behavioral FTD, bvFTD, Neary et al. (1998)), which causes changes in behavior and personality but leaves syntax, phonology and semantics relatively intact, and a variant that causes impairments in the language processing system (Primary Progessive Aphasia, PPA (Gorno-Tempini et al., 2004). PPA can be subdivided into subtypes fluent (fluent but empty speech, comprehension of word meaning is affected / `semantic dementia') and non-fluent (agrammatism, hesitant or labored speech, word finding problems). Some identify logopenic aphasia as a FTD-variant: fluent aphasia with anomia but intact object recognition and underlying word meaning."
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