I created many series featuring faces of different people at various ages with distinct looks. Additionally, there are graphical images of animals, such as a dog and a cat. All these images are graphical vector illustrations that have been simplified step by step in Illustrator. There are also more images of faces that I have manually created. Later, I used digital tools to simplify them gradually.
During the summer break, I plan to simplify these images further, until only two dots remain where the eyes used to be. Then, I want to conduct the same experiment again to validate the findings from my previous post. This is my collection of different faces in various stages of abstraction.
Series 01: Middle Aged Man
Series 02: Young Girl
Series 03: Young Boy
Series 04: Cat
Series 05: Dog
Series 06: Dot Art
Series 06: Line Art
Series 07: Print
Series 08: Profile Drawing
It was important to me to create a series that is highly diverse, encompassing a variety of styles and personalities. At the same time, I wanted to maintain a structured approach to the abstraction process, ensuring continuity in the simplification stages. This method will help me systematically explore how different degrees of abstraction affect the perception of faces and personalities, providing valuable insights for my ongoing research.
Face Detection: Understanding the Process and Its Impact
Multiple Face Detection in Images
Face recognition systems are emerging as one of the most promising applications in image analysis. As Dwivedi (2018) highlights, the field of image processing has experienced significant advancements in recent years. High-quality face recognition relies on various algorithms that extract, classify, and match facial features. This process also involves similarity or distance measures, where efficient matching can even improve existing feature extraction methods (El-Sayed & Hamed, 2015). However, factors such as pose, facial expression, lighting, orientation, skin color, the presence of glasses or facial hair, and image resolution introduce variability and complexity into face detection (Dwivedi, 2018).
A major breakthrough came with the development of real-time face detection systems, which can detect faces with high accuracy in real time, marking a significant leap in image processing. Face detection is a subset of object detection and represents the first essential step toward successful face recognition. Officially, face detection methods are categorized into four approaches:
Knowledge-Based
Feature-Based
Template Matching
Appearance-Based
How Face Detection Works
Face detection in systems like OpenCV follows a series of structured steps. First, the image is imported and converted from RGB to grayscale, as grayscale simplifies facial feature detection. Next, image manipulation and segmentation make it easier for classifiers to detect facial shapes. The widely-used Haar-Like Features Algorithm is then applied to locate human faces in the image. This algorithm detects common patterns in human faces, such as darker regions around the eyes and lighter regions around the nose. By focusing on these key features, the algorithm selects and extracts essential components for detecting faces.
Once the region of interest is defined, typically marked by the coordinates x, y, w, h, the face is enclosed in a rectangular box. Additional techniques like smile detection, eye detection, and blink detection can further enhance the accuracy and detail of the detection process.
Potential and Challenges of Face Recognition
On one hand, face recognition offers clear advantages by simplifying various processes. Automatic identification eliminates the need for passwords or manual log-ins, making daily operations more efficient. On the other hand, this convenience introduces risks, such as potential errors and privacy concerns. The possibility of misuse, particularly in sensitive areas like surveillance, highlights the need for careful implementation.
Face recognition can also be an asset in law enforcement, aiding in identifying criminals and improving public safety. However, the dystopian use of such technologies, like the social credit system in China, serves as a stark reminder of the ethical implications. When misused, face detection systems could lead to intrusive surveillance and loss of personal freedom.
Humanization in Design
Humanization in design is defined either as the process of making something more suitable and pleasant for people or as making non-human objects appear more human. Designers frequently apply this concept in their work, especially when designing facial features or shapes that evoke human-like qualities.
One fascinating phenomenon related to this is pareidolia, the tendency to perceive meaningful images in random or ambiguous visual patterns (Merriam-Webster, 2023). A classic example is the work of Giuseppe Arcimboldo, who created human portraits from collections of fruits and vegetables. Leonardo da Vinci also observed the human tendency to see patterns in randomness.
Vertumnus, Kaiser Rudolf II. 1590.
In modern times, we see pareidolia in everyday products, where people perceive face-like configurations. This perception influences consumer behavior, as the emotional content of these configurations can capture attention and affect purchasing decisions. Research shows that products with configurations resembling emotions like happiness, surprise, or anger capture more attention and encourage product exploration. However, only “happy” designs seem to consistently increase purchase intent (Noble, 2023). Understanding this psychological effect is crucial for designers, as leveraging pareidolia can enhance user experience, foster emotional connections with products, and drive consumer engagement.
“… if you look at any walls spotted with various stains or with a mixture of different kinds of stones, if you are about to invent some scene you will be able to see in it a resemblance to various different landscapes adorned with mountains, rivers, rocks, trees, wide valleys, and various groups of hills.”
El-Sayed, Mohamed, and Hamed Hossam. „Feature Extraction Techniques for Face Recognition.“ Journal of Software Engineering and Applications 8, no. 9 (September 2015). https://www.scirp.org/journal/home?journalid=45.
Noble, Erin. „Face Pareidolia in Products: The Effect of Emotional Content on Attention Capture, Eagerness to Explore, and Likelihood to Purchase.“ Applied Cognitive Psychology 37, no. 4 (July 2023). https://onlinelibrary.wiley.com/doi/10.1002/acp.4105.
Yang, Ming-Hsuan, Kriegman, David J., and Narendra Ahuja. „Detecting Faces in Images: A Survey.“ IEEE Transactions on Pattern Analysis and Machine Intelligence 24, no. 1 (2002): 34–58. https://doi.org/10.1109/34.982883.
The Effect of Humanisation and the Appearance of Facial Shapes in the Field of Design.
Throughout the history of graphic design, facial features have consistently reappeared as a significant element. Although the context and degree of abstraction have varied across different historical periods, it is clear that shapes resembling the human face have a distinctive character that particularly appeals to us. Faces are a rich source of information, providing insights into identity, state of mind, emotions, intentions, and other interpersonal factors (PubMed Central, July 2020). The phenomenon of „facial pareidolia,“ where our brains detect patterns, especially faces, in inanimate objects (Ouellette, Jennifer, 2021), is another intriguing aspect worth exploring.
Next my research, I intend to delve into the psychology of perception to gain a deeper understanding of how humans cognitively and emotionally perceive and interpret different kinds of faces. With this knowledge, I will analyse the design of notable modern and contemporary visual works on a more profound level. As starting points, I will examine creatives like Bruno Munari, who included “25 loose colored cards centered around the theme of faces” (Exile Book) in his book Design as Art, and Paul Rand’s works, like his logos designed for Esquire magazine in 1938 and the pictorial version for IBM in 1988. My goal is to understand how graphic designers utilise the humanisation of their work to communicate messages more effectively within their specific historical contexts. Ultimately, I aim to conduct experiments that will culminate in the production of my own creative work, incorporating elements of the human face.
Publications by Bruno Munari
Bruno Munari:, Multiple Identities of a Face, „Design as Art“, 1966Bruno Munari: „Look into my Eyes“, 1970
Logos with Facial Elements by Paul Rand
Logo with facial features designed by Paul Rand in 1938Pictorial version of Rand’s rebus from 1988
Sources:
Munari, Bruno. Design as Art. London: Penguin Books, 1966.
Oruc, Ipek, Benjamin Balas, and Michael Landy. “Face Perception: A Brief Journey Through Recent Discoveries and Current Directions.” Vision Research 157 (April 2019): 1–9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371014/.
