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The H.264 encoded video is highly sensitive to loss of motion vectors during transmission. Several statistical techniques are proposed for recovering such lost motion vectors. These use only the motion vectors that belong to the macroblocks that are horizontally or vertically adjacent to the lost macroblock, to recover the latter. Intuitively this is one of the main reasons behind why these techniques yield inferior solutions in scenarios where there is a non-linear motion. This paper proposes B-Spline based statistical techniques that comprehensively address the motion vector recovery problem in the presence of different types of motions that include slow, fast/sudden, continuous and non-linear movements. Testing the proposed algorithms with different benchmark video sequences shows an average improvement of up to 2 dB in the Peak Signal to Noise Ratio of some of the recovered videos, over existing techniques. A 2 dB improvement in PSNR is very significant from an application point of view.