A Method For Adding Motion-Blur on Arbitrary Objects By using Auto-Segmentation and Color Compensation Techniques
When dynamic objects are captured by a camera, motion blur inevitably occurs. Such a blur is sometimes considered as just a noise, however, it sometimes gives an important effect to add dynamism in the scene for photographs or videos. Unlike the similar effects, such as defocus blur, which is now easily controlled even by smartphones, motion blur is still uncontrollable and makes undesired effects on photographs. In this paper, an unified framework to add motion blur on per-object basis is proposed. In the method, multiple frames are captured without motion blur and they are accumulated to create motion blur on target objects. To capture images without motion blur, shutter speed must be short, however, it makes captured images dark, and thus, a sensor gain should be increased to compensate it. Since a sensor gain causes a severe noise on image, we propose a color compensation algorithm based on non-linear filtering technique for solution. Another contribution is that our technique can be used to make HDR images for fast moving objects by using multi-exposure images. In the experiments, effectiveness of the method is confirmed by ablation study using several data sets.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
We address the novel task of jointly reconstructing the 3D shape, texture, and motion of an object from a single motion-blurred image. While previous approaches address the deblurring problem only in the 2D image domain,…
DeblurringObjectSuper-ResolutionTranslationStereo Video Deblurring
Videos acquired in low-light conditions often exhibit motion blur, which depends on the motion of the objects relative to the camera. This is not only visually unpleasing, but can hamper further processing. With this pap…
DeblurringVideo DeblurringRetrieval Robust to Object Motion Blur
Moving objects are frequently seen in daily life and usually appear blurred in images due to their motion. While general object retrieval is a widely explored area in computer vision, it primarily focuses on sharp and st…
ObjectRetrievalLearning Blind Motion Deblurring
As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime. However, taking a quick shot frequently yields a blurry result due to unwan…
DeblurringPlanar Geometry and Image Recovery from Motion-Blur
Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work,…
Deblurring