WVSN is severely constricted to energy, as it deals with video data. The major activities that consume more energy in WVSN are the local data processing and transmission. Among these two, data transmission consumes more energy. Hence, a mechanism to reduce the energy consumption during data transfer is required and this issue is addressed by compressive sensing. This paper presents an energy conserving scheme that extracts the forepart from the background scene. The compressive measurements are dynamically computed by this work, which reduces the overhead and energy consumption. This work selects minimal yet, optimal compressive measurements and forwards it to the destination side. The destination side rebuilds it with the help of CoSaMP algorithm. The performance of the proposed approach is tested in terms of forepart detection accuracy and energy consumption analysis. The proposed approach shows better results and outperforms the existing approaches. © 2021 Taiwan Academic Network Management Committee. All rights reserved.