Developing a depth-based tracking systems for interactive playful environments with animals

© ACM 2015. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM. Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology (p. 59). http://dx.doi.org/10.1145/2832932.2837007.[EN] Digital games for animals within Animal Computer Interaction are usually single-device oriented, however richer interactions could be delivered by considering multimodal environments and expanding the number of technological elements involved. In these playful ecosystems, animals could be either alone or accompanied by human beings, but in both cases the system should react properly to the interactions of all the players, creating more engaging and natural games. Technologically-mediated playful scenarios for animals will therefore require contextual information about the game participants, such as their location or body posture, in order to suitably adapt the system reactions. This paper presents a depth-based tracking system for cats capable of detecting their location, body posture and field of view. The proposed system could also be extended to locate and detect human gestures and track small robots, becoming a promising component in the creation of intelligent interspecies playful environments.Work supported by the Spanish Ministry of Economy and Competitiveness and funded by the EDRF-FEDER (TIN2014-60077-R). The work of Patricia Pons has been supported by a national grant from the Spanish MECD (FPU13/03831). Alejandro Catalá also received support from a VALi+d fellowship from the GVA (APOSTD/2013/013). Special thanks to our cat participants, their owners, and our feline caretakers and therapistsPons Tomás, P.; Jaén Martínez, FJ.; Catalá Bolós, A. (2015). Developing a depth-based tracking systems for interactive playful environments with animals. ACM. https://doi.org/10.1145/2832932.2837007SJan Bednarik and David Herman. 2015. Human gesture recognition using top view depth data obtained from Kinect sensor.Excel. - Student Conf. Innov. Technol. Sci. IT, 1--8.Hrvoje Benko, Andrew D. Wilson, Federico Zannier, and Hrvoje Benko. 2014. Dyadic projected spatial augmented reality.Proc. 27th Annu. ACM Symp. User interface Softw. Technol. - UIST '14, 645--655.Alper Bozkurt, David L Roberts, Barbara L Sherman, et al. 2014. Toward Cyber-Enhanced Working Dogs for Search and Rescue.IEEE Intell. Syst. 29, 6, 32--39.Rita Brugarolas, Robert T. Loftin, Pu Yang, David L. Roberts, Barbara Sherman, and Alper Bozkurt. 2013. 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Towards a Wearer-Centred Framework for Animal Biotelemetry

The emerging discipline of Animal-Computer Interaction (ACI) aims to understand the relation between animals and technology in naturalistic settings, to design technology that can support animals in different contexts and to develop user-centred research methods and frameworks that enable animals to take part in the design process as legitimate contributors [11]. Given existing interspecies differences and communication barriers, measuring the behaviour of animals involved in ACI research can be instrumental to achieving any or all of these aims, as a way of gauging the animals’ patterns, needs and preferences. Indeed, measuring behaviour is a common practice among ACI researchers, who take various approaches to this task [5,15,17,24]. In this respect, the use of biotelemetry devices such as VHF tags and GPS trackers, or bio-logging and environmental sensors has a significant potential [22]. At the same time, biotelemetry has been used for many years in many areas of biological research. Biotelemetry is used to improve the quality of physiological and behavioural data collected from animals and in an attempt to reduce researchers’ intrusion in the animals’ habitat [2]. However, there is evidence that carrying biotelemetry tags may influence the bearer’s physiology and behaviour [20]. Such impacts interfere with the validity of recorded data [14] and the welfare of individual animal wearers [1,3,13]. Neither of these effects are compatible with the animal-centred perspective advocated by ACI, on both scientific and ethical grounds. Our analysis of current body-attached device design and biotelemetry-enabled studies points to a general lack of wearer-centred perspective. To address these issues, we have developed a framework to inform the design of wearer-centred biotelemetry interventions, in order to support the implementation of animal-centred research methodologies and design solutions in ACI and other disciplines

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Assessing machine learning classifiers for the detection of animals' behavior using depth-based tracking

[EN] There is growing interest in the automatic detection of animals' behaviors and body postures within the field of Animal Computer Interaction, and the benefits this could bring to animal welfare, enabling remote communication, welfare assessment, detection of behavioral patterns, interactive and adaptive systems, etc. Most of the works on animals' behavior recognition rely on wearable sensors to gather information about the animals' postures and movements, which are then processed using machine learning techniques. However, non-wearable mechanisms such as depth-based tracking could also make use of machine learning techniques and classifiers for the automatic detection of animals' behavior. These systems also offer the advantage of working in set-ups in which wearable devices would be difficult to use. This paper presents a depth-based tracking system for the automatic detection of animals' postures and body parts, as well as an exhaustive evaluation on the performance of several classification algorithms based on both a supervised and a knowledge-based approach. The evaluation of the depth -based tracking system and the different classifiers shows that the system proposed is promising for advancing the research on animals' behavior recognition within and outside the field of Animal Computer Interaction. (C) 2017 Elsevier Ltd. All rights reserved.This work is funded by the European Development Regional Fund (EDRF-FEDER) and supported by Spanish MINECO with Project TIN2014-60077-R. It also received support from a postdoctoral fellowship within the VALi+d Program of the Conselleria d'Educacio, Cultura I Esport (Generalitat Valenciana) awarded to Alejandro Catala (APOSTD/2013/013). The work of Patricia Pons is supported by a national grant from the Spanish MECD (FPU13/03831). Special thanks to our cat participants and their owners, and many thanks to our feline caretakers and therapists, Olga, Asier and Julia, for their valuable collaboration and their dedication to animal wellbeing.Pons Tomás, P.; Jaén Martínez, FJ.; Catalá Bolós, A. (2017). Assessing machine learning classifiers for the detection of animals' behavior using depth-based tracking. Expert Systems with Applications. 86:235-246. https://doi.org/10.1016/j.eswa.2017.05.063S2352468

Remote interspecies interactions: Improving humans and animals wellbeing through mobile playful spaces

[EN] Play is an essential activity for both humans and animals as it provides stimulation and favors cognitive, physical and social development. This paper proposes a novel pervasive playful environment that allows hospitalized children to participate in remote interspecies play with dogs in a dog daycare facility, while it also allows the dogs to play by themselves with the pervasive system. The aim of this playful interactive space is to help improving both children¿s and animal¿s wellbeing and their relationships by means of technologically mediated play, while creating a solid knowledge base to define the future of pervasive interactive environments for animals.This work is supported by the European Development Regional Fund (EDRF-FEDER), Spain and Spanish MINECO (TIN2014-60077-R). The work of Patricia Pons is supported by the Spanish MECD (FPU13/03831). Special thanks to the dogs and children who participated in our study, the dogs' owners and the children's families. The authors also gratefully acknowledge the teachers of the Unidad Pedagogica Hospitalaria La Fe and Oncologia Pediatrica La Fe and also Olga and Astrid from Buma's Doggy Daycare facility, for their invaluable support, collaboration and dedication.Pons Tomás, P.; Carrion-Plaza, A.; Jaén Martínez, FJ. (2019). Remote interspecies interactions: Improving humans and animals wellbeing through mobile playful spaces. Pervasive and Mobile Computing. 52:113-130. https://doi.org/10.1016/j.pmcj.2018.12.003S1131305

Developing for non-human users:Reflecting on practical implications in the ubiquitous computing era

Advances in modern technology, such as the Internet of Things (IoT) and ubiquitous computing, open up new exciting opportunities for technology for animals. This is evidenced by the explosion of products and gadgets available for pets, digital enrichment for captive animals in zoos, sensor based smart farming, etc. At the same time, the emerging discipline of Animal-Computer Interaction (ACI) marks a new era in the design and development of animal technologies, promoting a more animal-centric approach, considering the needs of the animal in the development process. In this article, we reflect on the ways in which ideas of animal-centric development may impact the development of technology for animals in practice. We start by looking at the process of development for and with animals, and propose a development model facilitating the principles of Agility, Welfare of Animals, and eXperts’ involvement (AWAX) within the development lifecycle. While promoting the animal-centric approach, it is important to acknowledge that an animal usually uses technology through humans and in a particular environment. We further extend the AWAX model to include considerations of the human in the loop and the environment, and discuss some practical implications of this view, including aspects such as security and privacy