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Wearable devices, e.g., smart glass and watch, could achieve fine-grained human-centric sensing nowadays, but still lack sufficient capacities to execute sophisticated data processing algorithms. This paper presents Outlet to explore the feasibility to leverage the available computing resources from user's ambience, e.g., from nearby smart phones, tablets, computers, Wi-Fi APs, and so on, to form a mobile computing edge. We can then outsource wearable computing tasks to this ambient edge to locally digest the sensory data for prompt user feedback and reaction, as it is perfectly located in user's vicinity. The Outlet design avoids the traditional offloading to the remote clouds, whose performance may highly depend on the high-speed Internet connectivity and availability. To enable the Outlet design, we identify three major challenges: context dependence, scattered resources, and resource dynamics, and propose a series of key techniques to address each of them. To examine Outlet's performance, we conduct extensive trace-driven evaluations and the results indicate promising performance achieved by Outlet, e.g., mostly within 97.6% to 99.5% closeness of the optimal performance and always outperforming the baseline approach under various system settings.