Talks - Alynne Ferreira: Graphs and Vogue Dance: using data structures to create choreographies

Vogue dance originated in New York during the 70s-80s, emerging from LGBTQ+ and Latin/Black communities through ballroom culture

Graphs can be used to create and map dance choreographies by representing poses and transitions as nodes and edges

Key graph concepts covered:

• Directed vs undirected graphs
• Connected vs disconnected graphs
• Complete vs incomplete graphs
• Trees and binary trees
• Nodes, edges, and degrees

Python libraries networkx and matplotlib can be used to implement and visualize graph-based choreographies

Deterministic Finite Automaton (DFA) can validate sequences of dance moves through:

• Initial states
• Final states
• Transition functions
• Input symbols

Choreography creation becomes systematic when mapped as a state machine:

• Poses become nodes/states
• Transitions between poses become edges
• Sequences can be validated

The approach combines technical concepts with artistic expression, demonstrating interdisciplinary applications of data structures

Future possibilities include:

• Implementing pose detection
• Adding machine learning
• Creating automated choreography validation
• Building digital dance coaching systems