Essays about: "Human pose estimation"
Showing result 6 - 10 of 28 essays containing the words Human pose estimation.
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6. Dense Foot Pose Estimation From Images
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : There is ongoing research into building dense correspondence between digital images of objects in the world and estimating the 3D pose of these objects. This is a difficult area to conduct research due to the lack of availability of annotated data. Annotating each pixel is too time-consuming. READ MORE
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7. Human pose estimation in low-resolution images
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This project explores the understudied, yet important, case of human pose estimation in low-resolution images. This is done in the use-case of images with football players of known scale in the image. Human pose estimation can mainly be done in two different ways, the bottom-up method and the top-down method. READ MORE
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8. Designing for Body Awareness : Exploring the Interaction Between Screen and Participant in Pre-Recorded Online Workouts
University essay from Malmö universitet/Institutionen för konst, kultur och kommunikation (K3)Abstract : This thesis explores how we might design the interaction between the screen and participant in a pre-recorded online workout to enhance body awareness. This thesis uses a user-centred design approach combined with autoethnographic research to address the challenges of pre-recorded video workouts. READ MORE
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9. Evaluation of 3D motion capture data from a deep neural network combined with a biomechanical model
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : Motion capture has in recent years grown in interest in many fields from both game industry to sport analysis. The need of reflective markers and expensive multi-camera systems limits the business since they are costly and time-consuming. READ MORE
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10. Unsupervised 3D Human Pose Estimation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The thesis proposes an unsupervised representation learning method to predict 3D human pose from a 2D skeleton via a VAEGAN (Variational Autoencoder Generative Adversarial Network) hybrid network. The method learns to lift poses from 2D to 3D using selfsupervision and adversarial learning techniques. READ MORE