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Wyner-Ziv video coding is a new compression paradigm based on two key Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. It shifts the complexity to the decoder, resulting in a low- complexity encoder suitable for mobile video communications and visual sensor networks. This paper presents an improved Wyner-Ziv video coding scheme for sensor network. An improved key frame encoding method based on the correlation noise model (CNM) is proposed, and then a 3DRS-assisted motion estimation algorithm and AOBMC technique are used to improve the rate-distortion performance of the codec. The results show that our coding scheme can achieve 2-4 dB gain compared to state-of-the-art TDWZ codec and be deployed over a real visual sensor platform.