Abstract: Data representing animated hair in a computer generated imagery (CGI) scene may be compressed by treating hair data as arrays of parameters. Hair data parameters may include control vertices, hair color, hair radius, and the like. A principal component analysis (PCA) may be performed on the arrays of hair data. PCA may yield new basis vectors, varying in length, with the largest basis vector corresponding to a new dimension with the largest variance in hair data. The hair data may be quantized based on the varying lengths of new basis vectors. The number of bits allocated for quantizing each new dimension corresponding to each new basis vector may be determined based on the relative lengths of new basis vectors, with more bits allocated to dimensions corresponding to longer basis vectors. The quantized hair data may be bit-packed and then compressed using lossless entropy encoding.