Abstract: Highlights•A novel method is proposed that combines both texture and shape features.•Face recognition models are built at different levels of data granularity.•Experimentation is based on two well-known benchmarks, FG-NET and MORPH.•Proposed method outperforms state of art recognition method on rank-1 accuracy.•Proposed models support the simulation of aging effects at future time points.
Loading