Clothing conveys a strong communicative message in terms of social signals, influencing the impression and behaviour of others towards a person; unfortunately, the nature of this message is not completely clear, and social signal processing approaches are starting to consider this problem. Wearable computing devices offer a unique perspective in this scenario, capturing fine details of clothing items in the same way we do during a social interaction, through ego-centered points of views. These clothing characteristics can be then employed to unveil statistical relations with personal impressions. This position paper investigates this novel research direction, individuating the main objectives, the possible problems, viable research strategies, techniques and expected results. This analysis gives birth to brand-new concepts such as clothing saliency, that is, those parts of garments more relevant for triggering personal impressions.