The implications of embodiment for behavior and cognition: animal and robotic case studies

In this paper, we will argue that if we want to understand the function of the brain (or the control in the case of robots), we must understand how the brain is embedded into the physical system, and how the organism interacts with the real world. While embodiment has often been used in its trivial meaning, i.e. 'intelligence requires a body', the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. A number of case studies are presented to illustrate the concept. These involve animals and robots and are concentrated around locomotion, grasping, and visual perception. A theoretical scheme that can be used to embed the diverse case studies will be presented. Finally, we will establish a link between the low-level sensory-motor processes and cognition. We will present an embodied view on categorization, and propose the concepts of 'body schema' and 'forward models' as a natural extension of the embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5

Privaatsust säilitava raalnägemise meetodi arendamine kehalise aktiivsuse automaatseks jälgimiseks koolis

Väitekirja elektrooniline versioon ei sisalda publikatsiooneKuidas vaadelda inimesi ilma neid nägemata? Öeldakse, et ei ole viisakas jõllitada. Õigus privaatsusele on lausa inimõigus. Siiski on inimkäitumises palju sellist, mida teadlased tahaksid uurida inimesi vaadeldes. Näiteks tahame teada, kas lapsed hakkavad vahetunnis rohkem liikuma, kui koolis keelatakse nutitelefonid? Selle välja selgitamiseks peaks teadlane küsima lapsevanematelt nõusolekut võsukeste vaatlemiseks. Eeldusel, et lapsevanemad annavad loa, oleks klassikaliseks vaatluseks vaja tohutult palju tööjõudu – mitu vaatlejat koolimajas iga päev piisavalt pikal perioodil enne ja pärast nutitelefoni keelu kehtestamist. Doktoritööga püüdsin lahendada korraga privaatsuse probleemi ja tööjõu probleemi, asendades inimvaatleja tehisaruga. Kaasaegsed masinõppe meetodid võimaldavad luua mudeleid, mis tuvastavad automaatselt pildil või videos kujutatud objekte ja nende omadusi. Kui tahame tehisaru, mis tunneb pildil ära inimese, tuleb moodustada masinõppe andmestik, kus on pilte inimestest ja pilte ilma inimesteta. Kui tahame tehisaru, mis eristaks videos madalat ja kõrget kehalist aktiivsust, on vaja vastavat videoandmestikku. Doktoritöös kogusingi andmestiku, kus video laste liikumisest on sünkroniseeritud puusal kantavate aktseleromeetritega, et treenida mudel, mis eristaks videopikslites madalamat ja kõrgemat liikumise intensiivsust. Koostöös Tehonoloogiainstituudi iCV laboriga arendasime välja videoanalüüsi sensori prototüübi, mis suudab reaalaja kiirusel hinnata kaamera vaateväljas olevate inimeste kehalise aktiivsuse taset. Just see, et tehisaru suudab tuletada videost kehalise aktiivsuse informatsiooni ilma neid videokaadreid salvestamata ega inimestele üldsegi näitamata, võimaldab vaadelda inimesi ilma neid nägemata. Väljatöötatud meetod on mõeldud kehalise aktiivsuse mõõtmiseks koolipõhistes teadusuuringutes ning seetõttu on arenduses rõhutatud privaatsuse kaitsmist ja teaduseetikat. Laiemalt vaadates illustreerib doktoritöö aga raalnägemistehnoloogiate potentsiaali töötlemaks visuaalset infot linnaruumis ja töökohtadel ning mitte ainult kehalise aktiivsuse mõõtmiseks kõrgete teaduseetika kriteerimitega. Siin ongi koht avalikuks aruteluks – millistel tingimustel või kas üldse on OK, kui sind jõllitab robot?  How to observe people without seeing them? They say it's not polite to stare. The right to privacy is considered a human right. However, there is much in human behavior that scientists would like to study via observation. For example, we want to know whether children will start moving more during recess if smartphones are banned at school? To figure this out, scientists would have to ask parental consent to carry out the observation. Assuming parents grant permission, a huge amount of labour would be needed for classical observation - several observers in the schoolhouse every day for a sufficiently long period before and after the smartphone ban. With my doctoral thesis, I tried to solve both the problem of privacy and of labor by replacing the human observer with artificial intelligence (AI). Modern machine learning methods allow training models that automatically detect objects and their properties in images or video. If we want an AI that recognizes people in images, we need to form a machine learning dataset with pictures of people and pictures without people. If we want an AI that differentiates between low and high physical activity in video, we need a corresponding video dataset. In my doctoral thesis, I collected a dataset where video of children's movement is synchronized with hip-worn accelerometers to train a model that could differentiate between lower and higher levels of physical activity in video. In collaboration with the ICV lab at the Institute of Technology, we developed a prototype video analysis sensor that can estimate the level of physical activity of people in the camera's field of view at real-time speed. The fact that AI can derive information about physical activity from the video without recording the footage or showing it to anyone at all, makes it possible to observe without seeing. The method is designed for measuring physical activity in school-based research and therefore highly prioritizes privacy protection and research ethics. But more broadly, the thesis illustrates the potential of computer vision technologies for processing visual information in urban spaces and workplaces, and not only for measuring physical activity or adhering to high ethical standards. This warrants wider public discussion – under what conditions or whether at all is it OK to have a robot staring at you?https://www.ester.ee/record=b555972

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Fundamental structures of dynamic social networks

Social systems are in a constant state of flux with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding spreading of influence or diseases, formation of friendships, and the productivity of teams. While there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the micro-dynamics of social networks. Here we explore the dynamic social network of a densely-connected population of approximately 1000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geo-location, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-minute time slices we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores are preceded by coordination behavior in the communication networks, and demonstrating that social behavior can be predicted with high precision.Comment: Main Manuscript: 16 pages, 4 figures. Supplementary Information: 39 pages, 34 figure

Sensor fusion in smart camera networks for ambient intelligence

This short report introduces the topics of PhD research that was conducted on 2008-2013 and was defended on July 2013. The PhD thesis covers sensor fusion theory, gathers it into a framework with design rules for fusion-friendly design of vision networks, and elaborates on the rules through fusion experiments performed with four distinct applications of Ambient Intelligence

Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios