1. Motion blur not working (merge node) - Blackmagic Forum • View topic
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2. Motion Blur and Depth of Field - GameGuru Forum
May 31, 2015 · GameGuru lets you build your own world, using easy to use, creative and enjoyable tools. Join the community and create together.
GameGuru lets you build your own world, using easy to use, creative and enjoyable tools. Join the community and create together.
3. Motion-blur-free camera system splitting exposure time - IEEE Xplore
Oct 7, 2008 · In this paper, a motion-blur-free camera system using multi-exposed images is proposed. Advances in image sensors enable a high-speed image ...
In this paper, a motion-blur-free camera system using multi-exposed images is proposed. Advances in image sensors enable a high-speed image readout, which makes it possible to capture multiple images within a normal exposure time. The proposed camera system captures three frames successively at long-short-long exposure times from the same scene. In order to obtain a high-quality image, we utilize the motion-based image merging algorithm that combines the shape information of objects in the under-exposed image captured at the short exposure time and the color information from two blurred images taken at the long exposure time. Simulation results show that the proposed multi-exposure camera system can provide high-quality images mitigating the motion blur.
4. Why phenomena of Ghosting and Motion Blur occur in photogrammetry
Dec 20, 2017 · Motion blur therefore appears on an individual aerial photo, while ghosting occurs when combining two aerial photos that form a stereo pair.
Why phenomena of Ghosting and Motion Blur occur in photogrammetry
5. Motion Blur Kernel Rendering Using an Inertial Sensor - MDPI
Feb 28, 2022 · We propose a novel method to synthesize blurry images from sharp images by analyzing the mechanisms of the thermal detector.
Various types of motion blur are frequently observed in the images captured by sensors based on thermal and photon detectors. The difference in mechanisms between thermal and photon detectors directly results in different patterns of motion blur. Motivated by this observation, we propose a novel method to synthesize blurry images from sharp images by analyzing the mechanisms of the thermal detector. Further, we propose a novel blur kernel rendering method, which combines our proposed motion blur model with the inertial sensor in the thermal image domain. The accuracy of the blur kernel rendering method is evaluated by the task of thermal image deblurring. We construct a synthetic blurry image dataset based on acquired thermal images using an infrared camera for evaluation. This dataset is the first blurry thermal image dataset with ground-truth images in the thermal image domain. Qualitative and quantitative experiments are extensively carried out on our dataset, which show that our proposed method outperforms state-of-the-art methods.
6. The visual motion blur elimination method for silicon nitride bearing ...
May 29, 2024 · ... mining method to propagate global features ... By combining the motion blur characteristics of silicon nitride bearing rollers, motion blur ...
7. Concatenating 2D Motion Blur? - We Suck Less - Steak Under Water
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I've been looking around for more information on this, but the Fusion Tool Reference only points at a part of the manual that I'm not sure actually exists (l…
8. High Inclusiveness and Accuracy Motion Blur Real-Time Gesture ...
Mining, Modelling, Molbank, Molecules, Multimodal Technologies and Interaction ... The loss is distinguished by combining global and local scales. The FPN ...
The combination of gesture recognition and aerospace exploration robots can realize the efficient non-contact control of the robots. In the harsh aerospace environment, the captured gesture images are usually blurred and damaged inevitably. The motion blurred images not only cause part of the transmitted information to be lost, but also affect the effect of neural network training in the later stage. To improve the speed and accuracy of motion blurred gestures recognition, the algorithm of YOLOv4 (You Only Look Once, vision 4) is studied from the two aspects of motion blurred image processing and model optimization. The DeblurGanv2 is employed to remove the motion blur of the gestures in YOLOv4 network input pictures. In terms of model structure, the K-means++ algorithm is used to cluster the priori boxes for obtaining the more appropriate size parameters of the priori boxes. The CBAM attention mechanism and SPP (spatial pyramid pooling layer) structure are added to YOLOv4 model to improve the efficiency of network learning. The dataset for network training is designed for the human–computer interaction in the aerospace space. To reduce the redundant features of the captured images and enhance the effect of model training, the Wiener filter and bilateral filter are superimposed on the blurred images in the dataset to simply remove the motion blur. The augmentation of the model is executed by imitating different environments. A YOLOv4-gesture model is built, which collaborates...
