Facial Landmarks Localization Estimation by Cascaded Boosted Regression

International audienceAccurate detection of facial landmarks is very important for many applications like face recognition or analysis. In this paper we describe an efficient detector of facial landmarks based on a cascade of boosted regressors of arbitrary number of levels. We define as many regressors as landmarks and we train them separately. We describe how the training is conducted for the series of regressors by supplying training samples centered on the predictions of the previous levels. We employ gradient boosted regression and evaluate three different kinds of weak elementary regressors, each one based on Haar features: non parametric regressors, simple linear regressors and gradient boosted trees. We discuss trade-offs between the number of levels and the number of weak regressors for optimal detection speed. Experiments performed on three datasets suggest that our approach is competitive compared to state-of-the art systems regarding precision, speed as well as stability of the prediction on video streams

Unified and Scalable Incremental Recommenders with Consumed Item Packs

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Towards conservation and sustainable use of an indigenous crop: A large partnership network enabled the genetic diversity assessment of 1539 fonio (Digitaria exilis) accessions

International audienceThe use of neglected and underutilized species (NUS) in agrosystems is a potential solution to the challenges arising from global change. These species could contribute to the equitable diversification of agricultural systems. Providing knowledge on their genetic diversity and fostering access to data and results is essential for the development of strong collaborative future research. The study addressed these issues by assessing the diversity of the largest fonio (Digitaria exilis) collection existing to date. Associated with a user-friendly Shiny application (https://shinyapps.southgreen.fr/ app/foniodiv), our results reinforce research efficiency and broaden the prospects for all actors involved in enhancing fonio and indigenous crops as valuable resources for the future