The main focus of video encoding in the past twenty years has been on video broadcasting. A video is captured and encoded by professional equipment and then watched on varying consumer devices. Consequently, the focus was to increase the quality and to keep down the decoder complexity. In more recent years we observe a shift in user behavior, from solely consuming video to also producing and sharing video. As opposed to professional cameras such constrained media devices are limited by the encoder complexity. This thesis addresses Distributed Video Coding (DVC) as a possible solution for very low complexity video encoding. Straightforward intra coding techniques at the encoder is combined with exploiting motion information at the decoder side. In particular, the thesis focuses on the problems that typically emerge when exploiting temporal correlation solely at the decoder. The thesis covers performance limitations of different DVC aspects, namely channel coding, motion estimation at the decoder and quantization. All proposed schemes focus on allowing real-time encoding. In channel coding, we investigate decoder-based modeling. In motion estimation at the decoder, we focus on true motion-based extrapolation. In quantization, we propose a trade-off between adaptivity and overhead. Finally, we compare the derived solutions for each DVC aspect with its counterpart in conventional video coding. We find that DVC can outperform intra coding with a similar encoder complexity. However, for a less constrained encoder complexity conventional inter coding outperforms DVC by a large margin.