According to the neural and mechanism substrates basal for face, processing has invented tremendous advancement throughout the last years. This era has not given enough evidence that non-face and face objects are processed in critically different ways as well as in critically discrete cortical spaces. Processing across attainable views of faces is complicated. Since faces vary their fettle, when they move around that is the frontal view and the profile. Secondly, faces self-occlude, for example, the nose.
Additionally, faces change over time and other faces, which are very similar, exists (Willis, 2013). Even though the processing of a face from a processing point of view has some subtleties that make it different from the processing of other objects that does not make it different. In support of this, when one trains an object detector, he or she usually assumes that the objects in the training set are also available or contained in the test. Scientists refer to this type of analysis as an open test, which can apply to both non-face objects and faces.
Holistic processing is the phenomenon best known in faces (Richler, Wong, & Gauthier, 2011). Most individuals see faces entirely, not as a nose, a pair of eyes, and a mouth. Coincidentally, holistic recognition takes place in other cases too. Additionally, it can even be learned. It emerges from an expert. When an expert in music observes some music words, he or she identifies them quickly compared to when a novice sees the same. This can best mean that face processing and other objects processing use holistic processing phenomenon.
Persike and his co-authors pointed out that there is face-specific recognition up to grownups that is not partaken by other shapes (Meinhardt-Injac, Persike, & Meinhardt, 2014). In the study, face objects and non-face objects were compared in young children, older children, and adolescents. The study showed that there was a progressive increase in corresponding exactness for both faces as well as non-face shapes from childhood to adolescence. However, in face processing, adult levels were not reached in the adolescent group. While with non-face objects where in this case watches were used, adolescents and adults processed them effectively. Inversion and context effects, commonly referred to as expedients of configures and holistic recognition, were circumscribed to the face at any period that was subjected to the test. This study argues that both shifts tap into front-specific recognition mechanism, which is not available with other patterns. The study further found that face and other objects recognition depends on the same recognition regimes.
Visual areas of the mind that take place in the processing of objects form recognition stream that strategize towards the semi-permanent lobe (Andrews, 2005). Challenges in processing, naming, and identifying different classes of shapes always result in harms to this side of the mind. Taking, for instance, if the inferior lobe is destroyed, the capability to single persons by their facial characteristics becomes impaired. However, these injuries do not affect the capacity of other objects. To the contrary, wounds to the other parts of the temporal lobe affect one’s ability to identify different objects but leave the ability to recognize faces intact. Besides, the functioning imaging studies reveal those various areas if the temporal chronological lobes are more answerable to faces compared to non-face objects.
Face processing is a fundamental and effortless convivial approach, which carries a fraction of a millisecond. It is separated from other objects at the functional level as suggested by Caldara and his co-authors (Caldara, et al., 2003). The authors of this article investigated modulation of the N170 front-sensitive component affiliated to the perception of the same-race faces and other-race faces in addition to variations in front and other objects processing, through the combination of varied approaches of event-affiliated potential (ERP) signal analysis. The authors found that N170 face component was the same for both race faces. However, other-race faces educed stronger intermediate occipital conditioning than same-race fronts. This showed that there is some similarity between face recognition and the processing of non-face objects.
The optical processing of objects is an impressively complicated problem that biological systems solve tirelessly (Tarr & Cheng, 2003). Object processing relies on one taxonomy that objects can be placed in different categories based on their visual appearance. Perpetually similar objects that share identical surface and shape properties can be grouped depending on their experience of entry level. As a result of this varied recognition levels, many researchers have accredited that there exist multiple recognition levels, each of which supports the recognition of different visual categories. The most common similarity has been that there live no different systems for face and other objects processing even though they are recognized at different recognition levels. This dichotomy is based on the intuitions such as inherence convivial importance of the faces and the complication of discriminating personal faces.
Visual cortex houses specific regions specialized for processing faces but not other types of objects (Leibo, Mutch, & Poggio, 2011). Each day, visual tasks require a competitively good non-generic to invariance transformations like the variations in illumination and viewpoint. Ideally, the 3D rotation of an object with one 3D structure for example faces is not equal to the 3D rotation of other classes of objects with separate 3D structures. Both transformations cannot be taken into account at once by the generic circuitry. This argument applies to all other non-transformations as well. Since the brain has to take into account these transformations in interpreting the visual world, it subsequently follows that the visual cortex must have a modular architecture. As it develops, not all objects have different 3D structures; some have structures similar to the face. This concludes that faces are to no variation to distinct objects from a processing point of view.
Controversy has been surrounding the thought that individual mortal cortical areas in the ventral occipitotemporal cortex which various scholars refer to as fusiform face area (FFA) and occipital face area (OFA) are specialized for face recognition (Haist, Lee, & Stiles, 2010). In a recent study, a localizer task was administered to 16 people to define face-selective regions within the ventral occipitotemporal lobe (VOT). These were, the FFA and the OFA and the object-selective regions within the lateral occipital complex (LOC). Out of the 16 participators, 15 participators showed a strong FFA while one produced a reliable OFA. The researchers concluded that faces were not different from any other remonstrate from a recessional point of the lookout.
The understanding of the mechanisms and dorsal substrates that determine visual processing has considerably progressed over the last three decades. Over this era, a lot of evidence has accumulated to the extent of convincing several researchers that remonstrates, and faces are recognized in fundamentally distinct approaches and critically different cortical zones. This has contributed to an apparent decouple amid prepositions of how humans operate and stand for the two types of objects. Wallis decided to take part in the recognition literature in a bid to conciliate what he knew concerning the two kinds of processing by considering the impacts of erudition (Wallis, 2013). He found out that the recognition process is impacted by common vulnerability to fixed impulse stratum. In his research, he found out that a single model of processing could lead various examples of representation linked with faces and other types of objects.
Is face processing different from the identification of other objects? This debate has been ongoing for a long time. Clarifying this fate can have critical theoretical effects. This is because; face processing is often used as a core type of field-specificity in brain and mind. To participate in this debate, Christian Gerlach and his fellow authors decided to carry out a study. In their research, ten persons with developmental prosopagnosia (DP), as well as other 20 control experiment individuals, were examined (Gerlach, Klargaard, & Starrfelt, 2016). The participants were asked to fix six facial duplications of their alikeness. The DP group failed to perform the task while the control experiment group managed to arrange the faces to perfection. The authors established that face recognition was not different from the processing of other objects.
Experience plays a significant role in identifying objects (Tanaka & Gauthier, 1997). Tanaka and Gauthier decided to examine if this statement is valid through the study of the recognition process of object experts. Through the aid of the definition, experts interact more with the objects in their discipline of expertise compared to their novices. Tanaka and Gauthier found that both object experts and face experts are similar in that both kinds of processing involve identification at different levels of abstraction. However, the issue is whether the same or varied mechanisms mediate the process of face recognition. Suggestions have it that faces are recognized holistically unlike the rest of the objects. To ascertain this, the authors subjected a group of individuals in a rapid naming task where they were to quickly and accurately label a stack of pictures having familiar faces and shared objects. In their study, they found out that the subjects preferred to recognize faces with proper name labels rather than basic level terms such as face or person just like the processing of the other objects. They concluded that faces are not varied from the rest of the non-face objects from a recognition point of view.
Individual processing is essential for keeping various convivial interactions in a group (Wang & Takeuchi, 2017). Face processing is one of the highly specialized cognitive abilities in individual recognition. Wang and Takeuchi used the mating preference system and the electric shock conditioning experiment to examine personal identification in a medaka fish. They found that signals near the face are fundamental. Medaka required extra time to process vertically inverted faces compared to shifted or inverted faces. This ability can be compared to special face inversion effect in human beings and other mammals. Extra patterns that were added to the front also did not affect the individual recognition. The findings from the study suggest that face recognition is similar to the processing of other objects.
Human beings identify objects at varying levels. Experts are font of identifying objects within their domain of working compared to non-experts (Scott, Tanaka, Sheinberg, & Curran, 2006). Many think that object processing involves a definite shift from primary to secondary levels with training. Unfortunately, the mechanisms underlying this definite shift with increases in perceptual expertise are unknown. In face recognition, the entry point also shifts from primary to a secondary level of abstraction. Currently, there is no supportive evidence to show that face processing is different from the processing of other objects.
From the above analysis, it is evident that there is no enough evidence to justify that faces are different from any other class of objects from a recognition point of view. The human face and other objects share several similarities. These similarities provide critical information on convivial interaction and communication (SoriaBauser, BorisSuchan, & IreneDaum, 2011). We generally agree that faces undergo configured processing. This recognition touches three mechanisms bonding to first, second relational data and holistic processing. All faces share the first order relation as their basic configuration. That is, eyes, nose and a mouth below the nose thus this objects (nose, eyes, mouth, and eyes) assist in the identification of the face.
Conclusion:
Face recognition is just an object recognition problem (Zhao, 2007). It is just that it is a particular object that is being processed. In general, unlike other typical objects that are treated, specific methods, which include feature extraction and pattern recognition, are used in face processing. This evidence shows that faces are no distinct to any other type of non-face objects from a processing point of view.
Face processing is a unique form of pattern processing for example nose, mouth, or ears (Datta & Banerjee, 2015). It involves many stages such as recognizing the face as familiar, working out where the face was lastly seen and many other more scenes. The general point is that these patterns are objects in their own making. For instance, the nose or the ears are objects. This clears the doubt that face processing is no distinct from other class of objects from a recognition point of view.
References:
Andrews, T. J. (2005). Visual Cortex: How Are Faces and Objects Represented? Current Biology, 451-453.
Caldara, R., Thut, G., Servoir, P., Michel, C., Bovet, P., & Renault, B. (2003). Face versus non-face object perception and the ‘other-race’ effect: a spatio-temporal event-related potential study. Clinical Neurophysiology, 515-528.
Datta, A. K., & Banerjee, P. K. (2015). Face Recognition and Recognition Theory and Practice. ResearchGate, Online. Retrieved from https://www.researchgate.net/publication/311901041_Face_Detection_and_Recognition_Theory_and_Practice
Gerlach, C., Klargaard, S. K., & Starrfelt, R. (2016). On the Relation between Face and Object Recognition in Developmental Prosopagnosia: No Dissociation but a Systematic Association. Plus One, Online. Retrieved from https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165561
Haist, F., Lee, K., & Stiles, J. (2010). Individuating faces and common objects produces equal responses in putative face-processing areas in the ventral occipitotemporal cortex. Frontiers in Human Neuroscience, Online.
Leibo, J. Z., Mutch, J., & Poggio, T. (2011). Why The Brain Separates Face Recognition From Object Recognition. Face_Invar_v08_cam_rdy.dv, 1-9.
Meinhardt-Injac, B., Persike, M., & Meinhardt, G. (2014). Development of Visual Systems for Faces and Objects: Further Evidence for Prolonged Development of the Face System. A Peer-Reviewed, Open Access Journal, Online. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4067275/
Richler, J. J., Wong, Y. K., & Gauthier, I. (2011). Perceptual Expertise as a Shift From Strategic Interference to Automatic Holistic Processing. Current Directions in Psychological Science, Online. Retrieved from https://www.sciencedaily.com/releases/2011/05/110504123.htm
Scott, L. S., Tanaka, J. W., Sheinberg, D. L., & Curran, T. (2006). A Reevaluation of the Electrophysiological Correlates of Expert Object Processing. Journal of Cognitive Neuroscience, 1-13.
SoriaBauser, D. A., BorisSuchan, & IreneDaum. (2011). Differences between perception of human faces and body shapes: Evidence from the composite illusion. ScienceDirect, 195-202.
Tanaka, J., & Gauthier, I. (1997). Expertise in object and face recognition. Mechanisms of Perceptual, 83-125.
Tarr, M. J., & Cheng, Y. D. (2003). Learning to See Faces and Objects. TRENDS in Cognitive Sciences, 23-30.
Wallis, G. (2013). Toward a unified model of face and object recognition in the human visual system. Frontiers in Psychology, Online. Retrieved from https://www.frontiersin.org/articles/10.3389/fpsyg.2013.00497/full
Wang, M.-Y., & Takeuchi, H. (2017). Individual recognition and the ‘face inversion effect’ in medaka fish. eLIFE, Online. Retrieved from https://elifesciences.org/articles/24728
Willis, G. (2013). Toward a Unified Model of Face and Object Recognition in the Human Visual System. Original Research Article, Online. Retrieved from https://www.frontiersin.org/articles/10.3389/fpsyg.2013.00497/full
Zhao, Y. (2007). What is the Difference Between Face Recognition and Object Recognition. ResearchGate, Online. Retrieved from Research Gate: https://www.researchgate.net/post/whats_the_difference_between_face_recognition_and-object_recognition
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