Cat@Log

Yonezawa, Kyoko; Miyaki, Takashi; Rekimoto, Jun

doi:10.1145/1690388.1690414

Cited by 28 publications

(3 citation statements)

References 3 publications

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“…As mentioned above, cat owners consider their cats friends and family [18], and want to know how and what the cats are doing [25]. Reasons to track pets are diverse.…”

Section: Reasons To Track Petsmentioning

confidence: 99%

Visualizing cat GPS data

Swagerman

Mancini

Nack

2018

Proceedings of the Fifth International Conference on Animal-Computer Interaction

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Domestic cats are usually allowed to roam freely outside without human supervision, which creates a new market for consumer GPS tracking devices. However, current GPS devices and the supporting interfaces and visualizations are usually created with a focus on dog owners. To acquire more insight into the needs of cat owners in relation to GPS devices for domestic cats, an iterative prototype-based study was conducted. This paper presents the requirements for the visualization of GPS data of domestic cats that were determined in collaboration with cat owners during the study. Interviews and multiple prototypes were used as tools to identify and refine these requirements and were mostly based on cat owners' concerns and curiosity for their cats' location. The most important requirements for a cat owner-centered GPS visualization were being able to request the live location and being alerted if the cat might be in trouble.

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“…As mentioned above, cat owners consider their cats friends and family [18], and want to know how and what the cats are doing [25]. Reasons to track pets are diverse.…”

Section: Reasons To Track Petsmentioning

confidence: 99%

Visualizing cat GPS data

Swagerman

Mancini

Nack

2018

Proceedings of the Fifth International Conference on Animal-Computer Interaction

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“…However, it does not monitor any activity nor gesture. Cat@Log (Yonezawa, Miyaki, & Rekimoto, 2009) is a non-commercial but more complete device. It consists of a cat collar device with several sensors: a camera, a GPS, an accelerometer, a Bluetooth module, battery and micro SD card.…”

Section: Wearable Tracking Systemsmentioning

confidence: 99%

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

Pons

Jaén

Catalá

2017

Expert Systems with Applications

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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 setups 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. Highlights: • Animal Computer Interaction studies could benefit from automatic behavior detection • Cats' body postures and orientation can be determined using depth-based information • Depth-based trackers offer promising accuracy rates classifying cats' postures

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“…Canine Amusement and Training [23] uses a wearable harness with attached IR emitters to detect the position and posture of the animal. Cat@Log [24] uses a cat collar device with several sensors: a camera, a GPS, an accelerometer, a Bluetooth module, battery and micro SD card. The camera provides videos of the cat's view, while the accelerometer data is used for activity recognition such as sleeping, jumping, walking or scratching.…”

Section: Related Workmentioning

confidence: 99%

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

Pons

Jaén

Catalá

2015

Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology

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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.

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Cat@Log

Cited by 28 publications

References 3 publications

Visualizing cat GPS data

Visualizing cat GPS data

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

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

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