Existing markerless motion capture methods often assume known backgrounds, static cameras, and sequence specific motion priors, limiting their application scenarios. Here we present a fully automatic method that, given multi-view videos, estimates 3D human pose and body shape. We take the recently proposed SMPLify method [12] as the base method and extend it in several ways. First we fit a 3D human body model to 2D features detected in multi-view images. Second, we use a CNN method to segment the person in each image and fit the 3D body model to the contours, further improving accuracy. Third we utilize a generic and robust DCT temporal prior to handle the left and right side swapping issue sometimes introduced by the 2D pose estimator. Validation on standard benchmarks shows our results are comparable to the state of the art and also provide a realistic 3D shape avatar. We also demonstrate accurate results on HumanEva and on challenging monocular sequences of dancing from YouTube.
constitutes the largest IMU dataset publicly available. We quantitatively evaluate our approach on multiple datasets and show results from a real-time implementation. DIP-IMU and the code are available for research purposes. 1
The continuing interest and progress in indigenous communities and local economies based on traditional, cultural, and ecological knowledge contributes to indigenous resilience. Here we report on an ongoing collaborative project investigating the process of renewal of cultural heritage through strengthening the roots of indigenous cultural traditions of knowledge and practice, and the changing concepts of tradition. The project investigates the various mechanisms for conserving indigenous culture: How the heritage of indigenous culture is reconstructed; how this heritage is related to the social frame and practice of everyday life; how power intervention affects the contestation of heritage; and in the context of heritage contestation, how cultural heritage turns into economic capital in the tourism economy of the community. The project explores the process of cultural heritagization of indigenous traditional knowledge through six individual projects in the areas of food and edible heritage, ethnic revival, weaving, solidarity economy, cultural ecotourism, and indigenous agro-products. In addition, the project examines the establishment of a constructive dialogue between the “traditional future”, cultural heritage literature and local practice in the interest of the consolidation of alternative development.
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