Emotion Visualizer

Emotion Visualizer is an innovative interactive installation designed to delve into the complex relationship between emotions and visual expression through machine learning. The project allows participants to sketch abstract shapes in response to their personal social media feeds. These sketches are analyzed by a machine learning model trained on a dataset of emotional responses collected previously. The system interprets the emotions depicted in the drawings, offering participants a detailed understanding of the emotions their artwork conveys. The primary objective of the “Emotion Visualizer” is to assist individuals who find it challenging to express their feelings verbally by providing a novel tool that helps to understand and explore their emotional complexities. This installation facilitates a deeper comprehension of one’s emotional landscape and promotes self-reconciliation. Through this exploration, the thesis aims to contribute to the broader discussions on the intersection of technology, art, and psychological well-being.

Why it matters?

Having witnessed the struggles of my previous cohort during my undergraduate years, I have come to recognize the profound impact art can have as a medium for emotional expression. Many of my peers found solace in channeling their feelings into their artwork, using colors, shapes, and forms to convey what words often failed to capture. Inspired by their experiences, I am motivated to leverage visual representations as a catalyst for encouraging individuals to embark on a journey of learning and self-discovery. By creating an interaction where emotions can be freely explored and communicated through drawing, I aim to foster a deeper connection between individuals and their inner selves. Through this process, I hope to help people understand the complexity of emotions, empowering them to initiate intimate conversations with their feelings and embracing them as valuable and insightful guides.