Patricia Pons

Envisioning Future Playful Interactive Environments for Animals

Play stands as one of the most natural and inherent behavior among the majority of living species, specifically humans and animals. Human play has evolved significantly over the years, and so have done the artifacts which allow us to play: from children playing tag games without any tools other than their bodies, to modern video games using haptic and wearable devices to augment the playful experience. However, this ludic revolution has not been the same for the humans’ closest companions, our pets. Recently, a new discipline inside the human–computer interaction (HCI) community, called animal–computer interaction (ACI), has focused its attention on improving animals’ welfare using technology. Several works in the ACI field rely on playful interfaces to mediate this digital communication between animals and humans. Until now, the development of these interfaces only comprises a single goal or activity, and its adaptation to the animals’ needs requires the developers’ intervention. This work analyzes the existing approaches, proposing a more generic and autonomous system aimed at addressing several aspects of animal welfare at a time: Intelligent Playful Environments for Animals. The great potential of these systems is discussed, explaining how incorporating intelligent capabilities within playful environments could allow learning from the animals’ behavior and automatically adapt the game to the animals’ needs and preferences. The engaging playful activities created with these systems could serve different purposes and eventually improve animals’ quality of life.

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

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.

A meta-model for dataflow-based rules in smart environments: Evaluating user comprehension and performance

A considerable part of the behavior in smart environments relies on event-driven and rule specification. Rules are the mechanism most often used to enable user customization of the environment. However, the expressiveness of the rules available to users in editing and other tools is usually either limited or the available rule editing interfaces are not designed for end-users with low skills in programming. This means we have to look for interaction techniques and new ways to define user customization rules. This paper describes a generic and flexible meta-model to support expressive rules enhanced with data flow expressions that will graphically support the definition of rules without writing code. An empirical study was conducted on the ease of understanding of the visual data flow expressions, which are the key elements in our rule proposal. The visual dataflow language was compared to its corresponding textual version in terms of comprehension and ease of learning by teenagers in exercises involving calculations, modifications, writing and detecting equivalences in expressions in both languages. Although the subjects had some previous experience in editing mathematical expressions on spreadsheets, the study found their performance with visual dataflows to be significantly better in calculation and modification exercises. This makes our dataflow approach a promising mechanism for expressing user-customized reactive behavior in Ambient Intelligence (AmI) environments. The performance of the rule matching processor was validated by means of two stress tests to ensure that the meta-model approach adopted would be able to scale up with the number of types and instances in the space.

Sound to your objects: a novel design approach to evaluate orangutans' interest in sound-based stimuli

Orangutans show interest in sound-based stimuli, but the auditory enrichment they are usually provided with is either based on human-music, or does not allow for control and choice. In this work-in-progress paper, we describe the design of sound-based enrichment by means of the manipulation of tangible non-technological elements. In doing so, we demonstrate how Animal Computer Interaction research can help in providing animals with more control over auditory stimuli, as well as demonstrating and justifying a novel modality for interaction based on orangutan behavior within our ongoing study. We overview our proposed evaluation, identifying how - through embodying notions of control and choice in design - our proposed system allows for orangutan use to inform ongoing development and design of auditory enrichment.

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

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.

Active Creation of Digital Games as Learning Tools

Digital media and software have been used in supporting learning. Activities based on games should place the emphasis on the phase of creating artifacts for the game world, not on just playing or consuming contents. This chapter briefly reviews a number of outstanding efforts on providing advanced systems for the creation of digital games or simulations by children or young users, and analyzes their characteristics in terms of technology and the creation degree offered in both authorship and play processes.

Playful Creativity: Playing to Create Games on Surfaces

Creativity is of vital importance for human development since it allows individuals and ultimately society to successfully overcome new challenges. Besides social factors, the environment can also influence the development of such an important skill. We therefore considered it of interest to explore this capacity in the context of new information technology and game-based learning. Tabletop systems greatly facilitate the characteristics behind creative processes such as communication, the exchange of ideas, and collaborative interaction between individuals. This chapter explores the suitability of interactive surfaces in collaborative creative tasks carried out by teenage students using software to create 2D game worlds for tabletops.

Where HCI meets ACI

This one day workshop examines the interactions and the space between HCI (Human Computer Interaction) and ACI (Animal Computer Interaction) focusing on the transferability of methods and ideas between the two fields. The workshop will begin with short presentations followed by plenary discussions. The aim is to strengthen connected thinking whilst highlighting the exchangeable connecting methods from both ACI and HCI and their subfields including Child Computer Interaction (CCI) and Human Robot Interaction (HRI), discussing what these fields learn from each other with their similarities and differences mapped. The output of this workshop will be an initial mapping of the ACI and HCI fields interchange of methods and learning transferability as well as an advanced understanding of how the two fields are useful to each other.