Detection of Double-Compressed Videos Using Descriptors of Video Encoders.

In digital forensics, video becomes important evidence in an accident or a crime. However, video editing programs are easily available in the market, and even non-experts can delete or modify a section of an evidence video that contains adverse evidence. The tampered video is compressed again and stored. Therefore, detecting a double-compressed video is one of the important methods in the field of digital video tampering detection. In this paper, we present a new approach to detecting a double-compressed video using the proposed descriptors of video encoders. The implementation of real-time video encoders is so complex that manufacturers should develop hardware video encoders considering a trade-off between complexity and performance. According to our observation, hardware video encoders practically do not use all possible encoding modes defined in the video coding standard but only a subset of the encoding modes. The proposed method defines this subset of encoding modes as the descriptor of the video encoder. If a video is double-compressed, the descriptor of the double-compressed video is changed to the descriptor of the video encoder used for double-compression. Therefore, the proposed method detects the double-compressed video by checking whether the descriptor of the test video is changed or not. In our experiments, we show descriptors of various H.264 and High-Efficiency Video Coding (HEVC) video encoders and demonstrate that our proposed method successfully detects double-compressed videos in most cases.

Low Memory Access Video Stabilization for Low-Cost Camera SoC.

Video stabilization is one of the most important features in consumer cameras. Even simple video stabilization algorithms may need to access the frames several times to generate a stabilized output image, which places a significant burden on the camera hardware. This high-memory-access requirement makes it difficult to implement video stabilization in real time on low-cost camera SoC. Reduction of the memory usage is a critical issue in camera hardware. This paper presents a structure and layout method to efficiently implement video stabilization for low-end hardware devices in terms of shared memory access amount. The proposed method places sub-components of video stabilization in a parasitic form in other processing blocks, and the sub-components reuse data read from other processing blocks without directly accessing data in the shared memory. Although the proposed method is not superior to the state-of-the-art methods applied in post-processing in terms of video quality, it provides sufficient performance to lower the cost of camera hardware for the development of real-time devices. According to my analysis, the proposed one reduces the memory access amount by 21.1 times compared to the straightforward method.

Effect of Mechanical Ventilation Mode Type on Intra- and Postoperative Blood Loss in Patients Undergoing Posterior Lumbar Interbody Fusion Surgery: A Randomized Controlled Trial.

BACKGROUND: The aim of study was to evaluate the effect of mechanical ventilation mode type, pressure-controlled ventilation (PCV), or volume-controlled ventilation (VCV) on intra- and postoperative surgical bleeding in patients undergoing posterior lumbar interbody fusion (PLIF) surgery. METHODS: This was a prospective, randomized, single-blinded, and parallel study that included 56 patients undergoing PLIF and who were mechanically ventilated using PCV or VCV. A permuted block randomization was used with a computer-generated list. The hemodynamic and respiratory parameters were measured after anesthesia induction in supine position, 5 min after patients were changed from supine to prone position, at the time of skin closure, and 5 min after the patients were changed from prone to supine position. The amount of intraoperative surgical bleeding, fluid administration, urine output, and transfusion requirement were measured at the end of surgery. The amount of postoperative bleeding and transfusion requirement were recorded every 24 h for 72 h. RESULTS: The primary outcome was the amount of intraoperative surgical bleeding, and 56 patients were analyzed. The amount of intraoperative surgical bleeding was significantly less in the PCV group than that in the VCV group (median, 253.0 [interquartile range, 179.0 to 316.5] ml in PCV group vs. 382.5 [328.0 to 489.5] ml in VCV group; P < 0.001). Comparing other parameters between groups, only peak inspiratory pressure at each measurement point in PCV group was significantly lower than that in VCV group. No harmful events were recorded. CONCLUSION: Intraoperative PCV decreased intraoperative surgical bleeding in patients undergoing PLIF, which may be related to lower intraoperative peak inspiratory pressure.

Video deblurring algorithm using accurate blur kernel estimation and residual deconvolution based on a blurred-unblurred frame pair.

Blurred frames may happen sparsely in a video sequence acquired by consumer devices such as digital camcorders and digital cameras. In order to avoid visually annoying artifacts due to those blurred frames, this paper presents a novel motion deblurring algorithm in which a blurred frame can be reconstructed utilizing the high-resolution information of adjacent unblurred frames. First, a motion-compensated predictor for the blurred frame is derived from its neighboring unblurred frame via specific motion estimation. Then, an accurate blur kernel, which is difficult to directly obtain from the blurred frame itself, is computed using both the predictor and the blurred frame. Next, a residual deconvolution is applied to both of those frames in order to reduce the ringing artifacts inherently caused by conventional deconvolution. The blur kernel estimation and deconvolution processes are iteratively performed for the deblurred frame. Simulation results show that the proposed algorithm provides superior deblurring results over conventional deblurring algorithms while preserving details and reducing ringing artifacts.