152,368 research outputs found

    Video face replacement

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    We present a method for replacing facial performances in video. Our approach accounts for differences in identity, visual appearance, speech, and timing between source and target videos. Unlike prior work, it does not require substantial manual operation or complex acquisition hardware, only single-camera video. We use a 3D multilinear model to track the facial performance in both videos. Using the corresponding 3D geometry, we warp the source to the target face and retime the source to match the target performance. We then compute an optimal seam through the video volume that maintains temporal consistency in the final composite. We showcase the use of our method on a variety of examples and present the result of a user study that suggests our results are difficult to distinguish from real video footage.National Science Foundation (U.S.) (Grant PHY-0835713)National Science Foundation (U.S.) (Grant DMS-0739255

    Personalised video instruction

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    The liaison librarian to a college with a substantial and growing online learning population began using asynchronous, personalised video instruction as an online replacement for the traditional face-to-face, one-on-one bibliographic instruction reference appointment. This project was informed by the framework of metaliteracy and the “See One, Do One, Teach One” instruction methodology utilised by the health sciences. While formal outcomes assessment has yet to be conducted, unsolicited comments from students are overwhelmingly positive, and preliminary data analysis of usage and engagement reveals several promising trends. 65% of all watched videos were watched for the entire duration of the video, and the liaison librarian found video creation to be less time-consuming than scheduling appointments. The liaison librarian to a university with a substantial and growing online learning population began using asynchronous, personalised video instruction as an online replacement for the traditional face-to-face, one-on-one bibliographic instruction reference appointment. This project was informed by the framework of metaliteracy and the ‘See One, Do One, Teach One’ instruction methodology utilised by the health sciences. While formal outcomes assessment has yet to be conducted, unsolicited comments from students are overwhelmingly positive, and preliminary data analysis of usage and engagement reveals several promising trends. Of all watched videos 65% were watched for the entire duration, and the liaison librarian found video creation to be less time-consuming than scheduling appointments. Providing personalised video instruction tailored to the individual student’s information literacy need is a novel approach that may benefit online learners and librarians alike

    Using Video as a Replacement or Complement for the Traditional Lecture/Demonstration Method in Agricultural Training in Rural Uganda

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    This study explored the effectiveness of video as a tool to either complement or replace existing lecture-demonstration training for small farmer groups. The effectiveness of video in decreasing the knowledge gap among farmers who differ by gender was also evaluated. Quantitative and qualitative data were gathered through a quasi-experiment including a pretest and a posttest design with three experimental groups. Results showed that video could be an effective complement and replacement for the traditional lecture-demonstration training method. Video alone or video plus traditional lecture-demonstration was as effective as traditional training in increasing learning. The training method that included both video and traditional lecture-demonstration was especially effective for groups with relatively low prior knowledge of the training topic. However, video only was not as effective as traditional training or traditional training plus video in decreasing gaps in learning between men and women. Video has advantages in rural areas because it does not require face-to-face presentation by skilled trainers. Video might be an attractive alternative or supplement if the production cost is low enough, or if traditional lecture-demonstration cannot meet the demand for training. Using local actors, shooting video in the local environment and using local languages add to video’s advantages for training purposes. When used to demonstrate a farming technique or practice in a group setting, videos were found to enhance interaction (e.g. discussion and peer learning) among farmers

    Testing the Effectiveness of Video to Complement or Replace the Lecture/demonstration Group Training Approach for Farmers in Kamuli District, Uganda

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    This study explored the effectiveness of video as a tool to either complement or replace existing lecture/demonstration training for small farmer groups. The effectiveness of video in decreasing the knowledge gap among farmers who differ by gender, bean production volume, and education level was also evaluated. Quantitative and qualitative data were gathered through a quasi-experiment including a pre-test and a post-test design with three experimental groups. Results showed that video could be an effective complement and replacement for the conventional lecture/demonstration training method. The training method that included both video and traditional lecture/demonstration was especially effective for groups with relatively low prior knowledge of the training topic. Video alone or video plus traditional lecture/demonstration were as effective as traditional training in decreasing gaps in learning among subjects of both genders, varying education levels and scales of bean planting. Video has advantages in rural areas because it does not require face-to-face presentation by skilled trainers. Video might be an attractive alternative or supplement if the production cost is low enough, or if conventional lecture/demonstration cannot meet the demand for training. Using local actors, shooting video in the local environment and using local languages add to video\u27s advantages for training purposes. When used to demonstrate a farming technique or practice in a group setting, videos were found to enhance interaction (e.g. discussion and peer learning) among farmers

    3D Human Face Reconstruction and 2D Appearance Synthesis

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    3D human face reconstruction has been an extensive research for decades due to its wide applications, such as animation, recognition and 3D-driven appearance synthesis. Although commodity depth sensors are widely available in recent years, image based face reconstruction are significantly valuable as images are much easier to access and store. In this dissertation, we first propose three image-based face reconstruction approaches according to different assumption of inputs. In the first approach, face geometry is extracted from multiple key frames of a video sequence with different head poses. The camera should be calibrated under this assumption. As the first approach is limited to videos, we propose the second approach then focus on single image. This approach also improves the geometry by adding fine grains using shading cue. We proposed a novel albedo estimation and linear optimization algorithm in this approach. In the third approach, we further loose the constraint of the input image to arbitrary in the wild images. Our proposed approach can robustly reconstruct high quality model even with extreme expressions and large poses. We then explore the applicability of our face reconstructions on four interesting applications: video face beautification, generating personalized facial blendshape from image sequences, face video stylizing and video face replacement. We demonstrate great potentials of our reconstruction approaches on these real-world applications. In particular, with the recent surge of interests in VR/AR, it is increasingly common to see people wearing head-mounted displays. However, the large occlusion on face is a big obstacle for people to communicate in a face-to-face manner. Our another application is that we explore hardware/software solutions for synthesizing the face image with presence of HMDs. We design two setups (experimental and mobile) which integrate two near IR cameras and one color camera to solve this problem. With our algorithm and prototype, we can achieve photo-realistic results. We further propose a deep neutral network to solve the HMD removal problem considering it as a face inpainting problem. This approach doesn\u27t need special hardware and run in real-time with satisfying results
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