An optimized complex motion prediction approach based on a video synopsis

PurposeThe space-time variants algorithm will not give good results in practical scenarios; when no tubes increase, these techniques will not give the results. It is challenging to reduce the energy of the output synopsis videos. In this paper, a new optimized technique has been implemented that models and covers every frame in the output video.Design/methodology/approachIn the video synopsis, condensing a video to produce a low frame rate (FR) video using their spatial and temporal coefficients is vital in complex environments. Maintaining a database is also feasible and consumes space. In recent years, many algorithms were proposed.FindingsThe main advantage of this proposed technique is that the output frames are selected by the user definitions and stored in low-intensity communication systems and also it gives tremendous support to the user to select desired tubes and thereby stops the criterion in the output video, which can be further suitable for the user's knowledge and creates nonoverlapping tube-oriented synopsis that can provide excellent visual experience.Research limitations/implicationsIn this research paper, four test videos are utilized with complex environments (high-density objects) and show that the proposed technique gives better results when compared to other existing techniques.Originality/valueThe proposed method provides a unique technique in video synopsis for compressing the data without loss.

New Low-Frame-Rate Compensating Pixel Circuit Based on Low-Temperature Poly-Si and Oxide TFTs for High-Pixel-Density Portable AMOLED Displays

A new low-frame-rate active-matrix organic light-emitting diode (AMOLED) pixel circuit with low-temperature poly-Si and oxide (LTPO) thin-film transistors (TFTs) for portable displays with high pixel density is reported. The proposed pixel circuit has the excellent ability to compensate for the threshold voltage variation of the driving TFT (ΔVTH_DTFT). By the results of simulation based on a fabricated LTPS TFT and a-IZTO TFT, we found that the error rates of the OLED current were all lower than 2.71% over the range of input data voltages when ΔVTH_DTFT = ±0.33 V, and a low frame rate of 1 Hz could be achieved with no flicker phenomenon. Moreover, with only one capacitor and two signal lines in the pixel circuit, a high pixel density and narrow bezel are expected to be realized. We revealed that the proposed 7T1C pixel circuit with low driving voltage and low frame rate is suitable for portable displays.

Research on Low Frame Rate Video Compression Algorithm in the Context of New Media

When using the current method to compress the low frame rate video animation video, there is no frame rate compensation for the video image, which cannot eliminate the artifacts generated in the compression process, resulting in low definition, poor quality, and low compression efficiency of the compressed low frame rate video animation video. In the context of new media, the linear function model is introduced to study the frame rate video animation video compression algorithm. In this paper, an adaptive detachable convolutional network is used to estimate the offset of low frame rate video animation using local convolution. According to the estimation results, the video frames are compensated to eliminate the artifacts of low frame rate video animation. After the frame rate compensation, the low frame rate video animation video is divided into blocks, the CS value of the image block is measured, the linear estimation of the image block is carried out by using the linear function model, and the compression of the low frame rate video animation video is completed according to the best linear estimation result. The experimental results show that the low frame rate video and animation video compressed by the proposed algorithm have high definition, high compression quality under different compression ratios, and high compression efficiency under different compression ratios.

Three-Dimensional Stereo Vision Tracking of Multiple Free-Swimming Fish for Low Frame Rate Video

Three-dimensional multiple fish tracking has gained significant research interest in quantifying fish behavior. However, most tracking techniques use a high frame rate, which is currently not viable for real-time tracking applications. This study discusses multiple fish-tracking techniques using low-frame-rate sampling of stereo video clips. The fish were tagged and tracked based on the absolute error of the predicted indices using past and present fish centroid locations and a deterministic frame index. In the predictor sub-system, linear regression and machine learning algorithms intended for nonlinear systems, such as the adaptive neuro-fuzzy inference system (ANFIS), symbolic regression, and Gaussian process regression (GPR), were investigated. The results showed that, in the context of tagging and tracking accuracy, the symbolic regression attained the best performance, followed by the GPR, that is, 74% to 100% and 81% to 91%, respectively. Considering the computation time, symbolic regression resulted in the highest computing lag of approximately 946 ms per iteration, whereas GPR achieved the lowest computing time of 39 ms.

Radiation Exposure Reduction and Patient Outcome by Using Very Low Frame Rate Fluoroscopy Protocol (3.8 + 7.5 fps) During Percutaneous Coronary Intervention

Objectives: In this study, we intend to analyze the feasibility and efficacy of very low frame rate fluoroscopy (VLFF) protocol using a combination of 3.8 and 7.5 fps while performing Percutaneous Coronary Intervention (PCI).Methods: A retrospective cohort including 193 patients undergoing PCI under the VLFF protocol (Post-VLFF group) was compared with a retrospective cohort of 133 patients, who underwent PCI prior to implementation of VLFF protocol (Pre-VLFF group). In the Pre-VLFF group, all PCIs were performed using fluoroscopy frame rate of 15 fps. In the Post-VLFF group, 3.8 fps was used to guide catheter engagement, coronary lesion wiring, pre-and post-dilation, and 7.5 fps was used for lesion assessment and stent placement. Increasing use of fluoroscopic storage in place of cineangiography was also encouraged. Cine acquisition in both groups was performed at 15 fps. Primary endpoint was radiation exposure measured by Air Kerma. Secondary endpoints were procedure related outcomes and patient related outcomes (Major Adverse Cardiac Events including all-cause mortality, Target Lesion Failure, Myocardial Infarction, and Stroke).RESULTS: Post-VLFF group showed 74.7% reduction in Air Kerma as compared to Pre-VLFF group (433 ± 27 mGy vs. 1,714 ± 140 mGy; p < 0.0001), with no increase in the fluoroscopy time (15.38 ± 0.98 min Post-VLFF vs. 17.06 ± 1.29 min Pre-VLFF; p = 0.529) and contrast volume (116.5 ± 4.9 ml Post-VLFF vs. 116.7 ± 6 ml Pre-VLFF; p = 0.700). Both groups had comparable procedural success and complications rates as well as incidence of MACE.Conclusions: The very low frame rate fluoroscopy protocol is a feasible, effective, and safe method to significantly reduce the radiation exposure during PCI without any compromise on procedural and patient outcomes.