Capturing human activities that involve both gross full-body mo- tion and detailed hand manipulation of objects is challenging for standard motion capture systems. We introduce a new method for creating natural scenes with such human activities. The input to our method includes motions of the full-body and the objects acquired simultaneously by a standard motion capture system. Our method then automatically synthesizes detailed and physically plausible hand manipulation that can seamlessly integrate with the input mo- tions. Instead of producing one “optimal” solution, our method presents a set of motions that exploit a wide variety of manipula- tion strategies. We propose a randomized sampling algorithm to search for as many as possible visually diverse solutions within the computational time budget. Our results highlight complex strate- gies human hands employ effortlessly and unconsciously, such as static, sliding, rolling, as well as finger gaits with discrete reloca- tion of contact points.