Underwater robots equipped with a single forward-looking camera usually have a very limited visual range or field-of-view (FOV) due to the light absorption and scattering effects in the underwater environment, which greatly limit their applications for underwater video-based inspection, navigation, and so on. Although underwater robots using multicamera imaging systems can achieve wide FOV of surroundings, parallax distortion and time-consuming stitching computation are encountered, especially for short-distance observation. To overcome these problems, we present a fast multicamera video-stitching algorithm based on adaptive adjustment of image transformation matrix between adjacent images. The proposed method uses a fast and adaptive optimization algorithm to search the optimal parameters of transformation matrix that can minimize the parallax distortion due to short-distance imaging and maximize the matching degree between adjacent overlapping image areas. The advantage of the proposed stitching method lies in that it avoids the complex and time-consuming computations for feature-point extraction and matching. The experimental results show that the proposed method can construct multicamera-based wide FOV video effectively and meets the real-time requirement of wide FOV video observation for both indoor and underwater scenes.