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Example of facial movement AU101 (inner brow raiser) in a domestic dog (Rhodesian Ridgeback, not a subject in the study), increasing the height and overall size of the orbital cavity (eye): A) neutral on right side of face, B) AU101 on right side of face.
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How wolves were first domesticated is unknown. One hypothesis suggests that wolves underwent a process of self-domestication by tolerating human presence and taking advantage of scavenging possibilities. The puppy-like physical and behavioural traits seen in dogs are thought to have evolved later, as a byproduct of selection against aggression. Usi...
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Accurate expression interpretation occupies a huge proportion of human-to-human communication. The control of expressions can facilitate more convenient communication between people. Expression recognition technology has also been transformed from relatively mature laboratory-controlled research to natural scenes research. In this paper, we design...
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... Action Descriptors (ADs) represent less precise or simultaneous multiple muscle contractions that affect facial morphology. While initially designed for human facial activity, this system has been adapted for eight species [12][13][14][25][26][27][28][29] . ...
Facial expressions in prey animals such as equines can convey information regarding their internal state and are therefore often used as cues for welfare and pain evaluation. The state of pain is commonly compared to a neutral state with little consideration given to other experiences that could affect the animal, although this situation is rare outside of experimental contexts. To evaluate the effect of managerial contexts on facial expressions from a nociceptive input, conspecific isolation and sedation with known physiological effects were compared to compound states of nociception. Using an anatomically based facial action coding system and a short acting pain model, patterns of facial activity could discriminate between horses experiencing conspecific isolation, sedation, and a nociceptive stimulus separately. Nociception occurring together with conspecific isolation could not be discriminated from the conspecific isolation alone, and compound nociception and sedation could not be discriminated from control. While blinking frequency demonstrated potential to be a valuable marker when evaluating a nociceptive stimulus in sedated horses, careful consideration must be given to the biological interpretation of facial expressions during situations where managerial or drug effects may be present.
... Following the same methodology as used for the human system, FACS has been modified for use with several other primate species: chimpanzees (ChimpFACS [5]), rhesus [6], Barbary [7], Japanese [8], and crested macaques [9] (MaqFACS), hylobatids (GibbonFACS [10]), orangutans (OrangFACS [11]), and common marmosets (CalliFACS [12]) and three domesticated species: dogs (DogFACS [13]), horses (EquiFACS [14]), and cats (CatFACS [15]). The adaptation of FACS for other species is based on the examination of anatomical homologies (e.g., [16][17][18]) while accounting for species differences in facial morphology. ...
... By applying these AnimalFACS tools, novel insights have been found about the communication systems of animals. For example, AnimalFACS have helped understand the manner in which dogs and cats communicate with humans [13,15,21] and how these species react facially in emotional contexts [22][23][24][25]. In NHP, AnimalFACS have also revealed the complexities of communication and emotion in a variety of species, including the fact that orangutan [26] and gibbon [27] play faces meet the behavioural criteria for intentionality, that the same facial expression in crested macaques (Silent-Bared Teeth) has different meanings depending on which AUs are included in the facial expression [9], that hylobatids pair-bonding is related to facial expressions [28], or that species previously thought to be less facially expressive, such as common marmosets, have a similar potential for facial movements as other NHP [12]. ...
... We tested inter-observer reliability between two FACS coders (CCC: certified in HumanFACS [2] and in all the AnimalFACS developed to date [5,6,8,[10][11][12][13][14][15]; RC: certified in ChimpFACS [5]) by coding 25 short videos (not used to describe the AUs). Inter-observer reliability was used to: (1) confirm both coders could reliably identify AUs included on the GorillaFACS manual, and (2) to refine the descriptions of AUs through discussion when agreement between coders on a particular AU was low. ...
The Facial Action Coding System (FACS) is an objective observation tool for measuring human facial behaviour. It avoids subjective attributions of meaning by objectively measuring independent movements linked to facial muscles, called Action Units (AUs). FACS has been adapted to 11 other taxa, including most apes, macaques and domestic animals, but not yet gorillas. To carry out cross species studies of facial expressions within and beyond apes, gorillas need to be included in such studies. Hence, we developed the GorillaFACS for the Gorilla spp. We followed similar methodology as previous FACS: First, we examined the facial muscular plan of the gorilla. Second, we analysed gorilla videos in a wide variety of contexts to identify their spontaneous facial movements. Third, we classified the individual facial movements according to appearance changes produced by the corresponding underlying musculature. A diverse repertoire of 42 facial movements was identified in the gorilla, including 28 AUs and 14 Action Descriptors, with several new movements not identified in the HumanFACS. Although some of the movements in gorillas differ from humans, the total number of AUs is comparable to the HumanFACS (32 AUs). Importantly, the gorilla’s range of facial movements was larger than expected, suggesting a more relevant role in social interactions than what was previously assumed. GorillaFACS is a scientific tool to measure facial movements, and thus, will allow us to better understand the gorilla’s expressions and communication. Furthermore, GorillaFACS has the potential be used as an important tool to evaluate this species welfare, particularly in settings of close proximity to humans.
... These landmark detection systems achieve a high level of accuracy when using high-quality video footage gathered in controlled environments [52]. Since a large portion of animalFACS studies are conducted in captive environments (including those with chimpanzees and domesticated cats; [18,22,23,30,43,55,56], these landmark detection techniques can be highly beneficial and dependable. Configuration data generated from our combinatorial models can be used to assess the accuracy of landmark detection outputs by determining the feasible combinations of facial muscle movements. ...
There has been an increased interest in standardized approaches to coding facial movement in mammals. Such approaches include Facial Action Coding Systems (FACS), where individuals are trained to identify discrete facial muscle movements that combine to create a facial configuration. Some studies have utilized FACS to analyze facial signaling, recording the quantity of morphologically distinct facial signals a species can generate. However, it is unclear whether these numbers represent the total number of facial muscle movement combinations (which we refer to as facial configurations) that each species is capable of producing. If unobserved combinations of facial muscle movements are communicative in nature, it is crucial to identify them, as this information is important for testing research hypotheses related to the evolution of complex communication among mammals. Our study aimed to assess how well the existing literature represents the potential range of facial signals in two previously studied species: chimpanzees (Pan troglodytes) and domesticated cats (Felis silvestris catus). We adhered to the coding guidelines outlined in the FACS manuals, which are based on the anatomical constraints and capabilities of each mammal’s face, to create our comprehensive list of all potential facial configurations. Using this approach, we found that chimpanzees and domesticated cats may be capable of producing thousands of facial configurations, many of which have not yet been documented in the existing research literature. It is plausible that some of these facial configurations are communicative and could be discovered with further research and video recording. In addition to our findings having significant implications for future research on the communicative complexity of mammals, it can also assist researchers in evaluating FACS coding accuracy.
... Dichas adaptaciones han sido establecidas por medio de modificaciones en la morfología facial de estos animales 8 y son el resultado de su domesticación 9,10 . Uno de estos cambios es el desarrollo del músculo Angulo occuli medialis, el cual provoca la elevación de la ceja 5 creando una percepción de ojos más grandes, aparentando así, un rostro infantil, dando a esta expresión mayor empatía para los humanos 11 . Por otro lado, se ha identificado que los caninos pueden experimentar las mismas emociones humanas, debido a un fenómeno denominado contagio emocional 12 , sugiriendo que el perro posee cierta capacidad de identificar los gestos faciales independientemente de la especie (humana o canina) 13 por lo cual puede responder con expresiones similares o contrarias, como una forma de agradecimiento o rechazo hacia las personas 14 . ...
... Humans may choose some features that are thought to be associated with an infantile aesthetic, such as bigger eyes and a larger space between the eyes [118]. Also, dogs that can enhance paedomorphism (change the eye size and height by raising the inner brow) through greater facial flexibility are found to be more desirable to humans [119]. Additionally, the animal's age also potentially affects people's decisions on whether or not to have a dog. ...
Dogs and cats have become the most important and successful pets through long-term domestication. People keep them for various reasons, such as their functional roles or for physical or psychological support. However, why humans are so attached to dogs and cats remains unclear. A comprehensive understanding of the current state of human preferences for dogs and cats and the potential influential factors behind it is required. Here, we investigate this question using two independent online datasets and anonymous questionnaires in China. We find that current human preferences for dog and cat videos are relatively higher than for most other interests, video plays ranking among the top three out of fifteen interests. We also find genetic variations, gender, age, and economic development levels notably influence human preferences for dogs and cats. Specifically, dog and cat ownership are significantly associated with parents’ pet ownership of dogs and cats (Spearman’s rank correlation coefficient is 0.43, 95% CI: 0.38–0.47), and the primary reason is to gain emotional support. Further analysis finds that women, young people, and those with higher incomes are more likely to prefer dog and cat videos. Our study provides insights into why humans become so attached to dogs and cats and establishes a foundation for developing co-evolutionary models.
... Facial expression analysis has also been applied to dogs using the dog facial action coding system ("DogFACS") (Waller et al., 2013). Bremhorst et al. (2019) examined the facial expressions of 29 Labrador Retrievers under positive and negative conditions, with food rewards used to induce positive anticipation and the absence of rewards to induce frustration. ...
The pet food industry is a growing business launching a variety of new products in the market. The acceptability or preference of pet food samples has traditionally been measured using either one‐bowl or two‐bowl tests. Academic researchers and professionals in the pet food industry have explored other methods, including the cognitive palatability assessment protocols and the ranking test, to evaluate more than two samples. A variety of approaches and perspectives were also utilized to predict palatability and key sensory attributes of pet foods, including descriptive sensory analysis by human‐trained panelists and pet food caregivers’ perceptions of pet food. This review article examined a range of testing methods for evaluating the palatability of pet foods, specifically targeting products for dogs and/or cats. It outlined the advantages and disadvantages of each method. Additionally, the review provided in‐depth insights into the key sensory attributes of pet foods and the methodologies for assessing palatability. It also explored pets’ behavioral responses and facial expressions in relation to different pet foods. Furthermore, this review discussed current challenges and future opportunities in pet food development, including the use of instrumental analyses and artificial intelligence–based approaches.
... Specifically, these videos were chosen under behaviourally defined conditions expected to elicit specific emotions, such as fearful responses during thunderstorms and frustrated responses after a first attempt to gain access to the resource and during its subsequent denials (see Table 1 for details). The putative emotion eliciting stimulus was evident for each original clip, and the core facial action units of each emotion were clearly identifiable through DogFACS (Dog Facial Action Coding System; Waller et al., 2013). All chosen dog expression clips were confirmed by two specialist authors, CC (trained coder in DogFACS) and DM (specialist in veterinary behavioural medicine). ...
... Unlike chimpanzees, our closest living relatives, dogs are uniquely adapted to read and process human facial expressions and gestures, and humans are better at reading dog facial expression than we are at reading chimpanzee expression (Correia-Caeiro et al., 2020;Hare et al., 2002;Kaminski & Nitzschner, 2013;Sullivan et al., 2022). Recent studies have demonstrated that humans place high value on specific movements of the eye region in domestic dogs that are not produced by gray wolves (Waller et al., 2013). It is becoming increasingly clear that humans selected specific traits during domestication, be it consciously or not, that focused on facilitating facial communication between humans and dogs (Correia-Caeiro et al., 2020;G acsi et al., 2004;Hare & Tomasello, 2005;Kaminski et al., 2019;Kaminski & Nitzschner, 2013;Mikl osi & Top al, 2013;Waller et al., 2013). ...
... Recent studies have demonstrated that humans place high value on specific movements of the eye region in domestic dogs that are not produced by gray wolves (Waller et al., 2013). It is becoming increasingly clear that humans selected specific traits during domestication, be it consciously or not, that focused on facilitating facial communication between humans and dogs (Correia-Caeiro et al., 2020;G acsi et al., 2004;Hare & Tomasello, 2005;Kaminski et al., 2019;Kaminski & Nitzschner, 2013;Mikl osi & Top al, 2013;Waller et al., 2013). ...
... Dog facial musculature morphology is divergent from that of gray wolves (Burrows et al., 2021;Kaminski et al., 2019). For example, Kaminski et al. (Waller et al., 2013) found that domestic dogs typically have musculature around the eye region that gray wolves seem to not have. Studies on facial musculature can inform our understanding of what movements both dogs and wolves can make with their faces. ...
Domestic dogs (Canis familiaris) are descended from gray wolf (Canis lupus) populations that inhabited Western Europe and Siberia. The specific timing of dog domestication is debated, but archeological and genetic evidence suggest that it was a multi‐phase process that began at least 15,000 years ago. There are many morphological differences between dogs and wolves, including marked divergence in facial muscle morphology, but we know little about the comparative physiology of these muscles. A better understanding of comparative facial muscle physiology between domestic dogs and gray wolves would improve our conceptual framework for the processual mechanisms in dog domestication. To address these issues, we assessed the myosin profiles (type I and type II) from the zygomaticus and orbicularis oris muscles of 6 domestic dogs and 4 gray wolves. Due to small sample sizes, statistical analyses were not done. Results reveal that sampled domestic dogs have almost 100% fast‐twitch (type II) muscle fibers while gray wolves have less than 50%, meaning that dog faces can contract fast while wolf faces are able to sustain facial muscle contraction. Sample sizes are limited but the present study indicates that dog domestication is associated with not only a change in facial muscle morphology but a concomitant change in how these muscles function physiologically. Selective pressures in the development of communication between dogs and humans using facial expression may have influenced this evolutionary divergence, but the paedomorphic retention of barking in adult dogs may have also played a role.
... Dogs (Canis familiaris) were domesticated from wolf-like Canis ancestors approximately 33 000 years ago [11]. During the domestication process, dogs evolved unique adaptations associated with their relationship to humans, including more fluid reproductive behaviour, paedomorphic facial features and hyper-social behaviour [12][13][14]. Furthermore, the facial muscles of dogs have been well described, in direct contrast to most mammals [15]. ...
... The dog's ability to make 'puppy dog eyes' has received a lot of attention over the last decade. The 'puppy dog eyes' expression is controlled by the levator anguli occuli medialis (LAOM) muscle, which originates on the frontal bone and attaches to the medial skin of the eyebrow and acts to raise the inner eyebrow [13,[22][23][24]. By raising the inner brows, the height of the orbital cavity appears to increase, which makes the eyes seem larger. ...
... By raising the inner brows, the height of the orbital cavity appears to increase, which makes the eyes seem larger. Together these two actions result in the inner brow raiser facial expression, creating the iconic 'puppy dog eyes' [13]. Therefore, when species like dogs have the LAOM, it suggests the species can create the inner brow raiser expression by contracting this muscle [13,22,25]. ...
Facial expressions are critical for non-verbal communication. The Canis genus epitomizes the interplay between behaviour and morphology in the evolution of non-verbal communication. Recent work suggests that the levator anguli oculi medialis (LAOM) muscle is unique to dogs (Canis familiaris) within the Canis genus and evolved due to domestication. The LAOM raises the inner eyebrows, resulting in the ‘puppy dog eyes’ expression. Here, we test whether the LAOM is a derived trait in dogs by (i) examining the facial expression muscles of a closely related and ancestral wild Canis species, the coyote (C. latrans) and (ii) comparing our results with other Canis and canid taxa. We discover that coyotes have a well-developed LAOM like dogs, which differs from the modified/absent LAOM in grey wolves. Our findings challenge the hypothesis that the LAOM developed due to domestication. We suggest that the LAOM is a basal trait that was lost in grey wolves. Additionally, we find inter- and intraspecific variations in the size of the muscles of the outer ear, forehead, lips and rostrum, indicating potential adaptations related to sensory perception, communication and individual-level functional variations within canids. Together, this research expands our knowledge of facial expressions, their evolution and their role in communication.
... It enabled the objective and systematic recognition of individual facial movements based Developing species-specific AnimalFACS involved identifying and documenting every potential facial movement of the species based on observable changes in appearance, consistent with the FACS terminology. Subsequently, the muscular foundation of each movement was confirmed through rigorous anatomical studies (56,61,63). This extensive work has interestingly unveiled phylogenetic similarities across species, with those already analyzed for FACS demonstrating a shared muscular foundation of at least 47% of their facial muscles (65). ...
Facial expressions are essential for communication and emotional expression across species. Despite the improvements brought by tools like the Horse Grimace Scale (HGS) in pain recognition in horses, their reliance on human identification of characteristic traits presents drawbacks such as subjectivity, training requirements, costs, and potential bias. Despite these challenges, the development of facial expression pain scales for animals has been making strides. To address these limitations, Automated Pain Recognition (APR) powered by Artificial Intelligence (AI) offers a promising advancement. Notably, computer vision and machine learning have revolutionized our approach to identifying and addressing pain in non-verbal patients, including animals, with profound implications for both veterinary medicine and animal welfare. By leveraging the capabilities of AI algorithms, we can construct sophisticated models capable of analyzing diverse data inputs, encompassing not only facial expressions but also body language, vocalizations, and physiological signals, to provide precise and objective evaluations of an animal's pain levels. While the advancement of APR holds great promise for improving animal welfare by enabling better pain management, it also brings forth the need to overcome data limitations, ensure ethical practices, and develop robust ground truth measures. This narrative review aimed to provide a comprehensive overview, tracing the journey from the initial application of facial expression recognition for the development of pain scales in animals to the recent application, evolution, and limitations of APR, thereby contributing to understanding this rapidly evolving field.