#visualperception

Teoría d la percepción. Escuela de la Gestalt. "Principio o Ley de Figura-Fondo"

"Esta es la cualidad de nuestra percepción por la cual configuramos un fondo en una forma, y una forma en un fondo". El ejemplo más popularmente conocido es el de dos caras simétricas cuyos perfiles nos ayudan a configurar una copa.- Ahora.- ¿Cuál de los elementos consideramos como forma y cuál como fondo?

La imagen de Morticia y Frankenstein bajo una luna que les observa, solo es un simple juego de elementos basado en este principio y en otros principios de la Gestalt

Introduction

Have you ever noticed that some images appear sharper, cleaner, or more “natural” than others—even when their resolution is the same? This phenomenon is deeply rooted in human visual perception. The way we interpret images is not just about pixels, but about how our brain processes contrast, color, edges, and patterns.

Understanding this can help explain why different image formats and processing methods lead to different visual experiences.

How the Human Eye Interprets Images

The human visual system is optimized for efficiency, not perfection. Instead of capturing every detail equally, our eyes and brain prioritize:

Edges and contrast

Brightness differences

Color transitions

Recognizable patterns

This is why we are more sensitive to sharp edges than to subtle color variations.

The Role of Compression in Perceived Quality

Image compression techniques often rely on the limitations of human perception.

For example:

Fine color details may be reduced without noticeable impact

Sharp edges are preserved because they are more visually important

Smooth gradients may be simplified

This explains why compressed images can appear nearly identical to original ones—even when data has been removed.

Transparency, Backgrounds, and Visual Context

One major factor affecting how an image looks is background context.

Transparent images (commonly stored in PNG format) can blend seamlessly into different designs

Images with solid backgrounds (often in JPEG format) may appear more consistent but less flexible

When transparency is no longer needed, converting an image to a format optimized for size and compatibility can be beneficial.

In practical workflows, this often involves converting images into more lightweight formats for easier sharing and faster loading. For example, browser-based tools such as https://www.pngtojpgonline.com demonstrate how images can be transformed efficiently while maintaining acceptable visual quality.

File Size vs Perceived Clarity

Interestingly, a larger file size does not always mean a clearer image.

Perceived clarity depends on:

Sharpness of edges

Contrast levels

Absence of visible artifacts

Viewing conditions (screen size, lighting, distance)

A well-compressed image can often look just as good as a much larger one when viewed under normal conditions.

The Importance of Context in Image Use

Different scenarios require different visual priorities:

Web design: prioritize fast loading and responsiveness

Photography: prioritize detail and color accuracy

UI/UX design: prioritize clarity and scalability

Social media: balance quality with upload speed

Choosing the right format and compression method depends heavily on how and where the image will be used.

Conclusion

Visual clarity is not just a technical property—it is a perceptual experience shaped by how humans process visual information. By understanding the relationship between image data and perception, we can make smarter decisions about how images are stored, optimized, and displayed.

For this exercise, I explored trompe-l’oeil, which is about creating an illusion that tricks the human eye. The idea is to make something flat or simple look more real or three-dimensional than it actually is. This interested me because VFX is mostly about illusion and how the viewer perceives space.

I wanted to understand how the human eye reacts to light, shadow, and perspective, and how small changes can completely change the way we read an image.

Process

I started by looking at real examples of trompe-l’oeil in paintings and architecture, where artists use light and perspective to create fake depth. I then tried to apply the same idea in 3D.

I used Maya and Blender to experiment with simple forms. I focused more on camera angle and lighting rather than complex modeling. By changing the camera position and light direction, I could make the scene feel deeper or flatter without changing the geometry.

Challenges

One challenge was that the scene often looked very flat when the lighting was too even. It didn’t feel convincing. To fix this, I adjusted the light angle and added stronger shadows. This helped the shapes stand out and improved the illusion.

Another issue was camera placement. A small camera movement made a big difference in how the scene was perceived.

Reflection / Learning

This exercise helped me realise that realism in VFX doesn’t always come from detail, but from how the human eye reads an image. Even simple shapes can look believable if the lighting and perspective are right.

A key decision in this project was fixing the camera at an approximate human eye level. By locking the camera position, I was able to adjust the depth and scale of the architecture to create a Trompe L’oeil illusion. The illusion works only from this viewpoint, which reflects how human perception depends on position and perspective.

This project explores Trompe L’oeil through architectural space, focusing on how the human eye perceives depth and illusion. The environment was designed from a fixed eye-level viewpoint using perspective and lighting. This work reflects my learning during the 3D VFX module.