Boosting multi-features with prior knowledge for mini unmanned helicopter landmark detection

Without sufficient real training data,the data driven classification algorithms based on boosting method cannot solely be utilized to applications such as the mini unmanned helicopter landmark image detection.In this paper,we propose an approach which uses a boosting algorithm with the prior knowledge for the mini unmanned helicopter landmark image detection.The stage forward stagewise additive model of boosting is analyzed,and the approach how to combine it with the prior knowledge model is presented.The approach is then applied to landmark image detection,where the multi-features are boosted to solve a series of problems,such as rotation,noises affected,etc.Results of real flight experiments demonstrate that for small training examples the boosted learning system using prior knowledge is dramatically better than the one driven by data only.

Robust facial landmark detection and tracking across poses and expressions for in-the-wild monocular video

We present a novel approach for automatically detecting and tracking facial landmarks acrossposesandexpressionsfromin-the-wild monocular video data,e.g.,You Tube videos and smartphone recordings.Our method does not require any calibration or manual adjustment for new individual input videos or actors.Firstly,we propose a method of robust 2D facial landmark detection across poses,by combining shape-face canonical-correlation analysis with a global supervised descent method.Since 2D regression-based methods are sensitive to unstable initialization,and the temporal and spatial coherence of videos is ignored,we utilize a coarse-todense 3D facial expression reconstruction method to refine the 2D landmarks.On one side,we employ an in-the-wild method to extract the coarse reconstruction result and its corresponding texture using the detected sparse facial landmarks,followed by robust pose,expression,and identity estimation.On the other side,to obtain dense reconstruction results,we give a face tracking flow method that corrects coarse reconstruction results and tracks weakly textured areas;this is used to iteratively update the coarse face model.Finally,a dense reconstruction result is estimated after it converges.Extensive experiments on a variety of video sequences recorded by ourselves or downloaded from You Tube show the results of facial landmark detection and tracking under various lighting conditions,for various head poses and facial expressions.The overall performance and a comparison with state-of-art methods demonstrate the robustness and effectiveness of our method.

Advanced Self-Localization and Navigation for Mobile Robots in Extraterrestrial Environments

Self-localization is one of the most important aspects for using mobile robots in unstructured environments. In this paper, the authors introduce a new approach for a self-localization and navigation unit for mobile platforms in extraterrestrial environments, based on the authors＂ successful results in self-localization of forestry machines on earth. The presented approach is developed from a highly modular concept, which allows a simple but efficient adaption to specific applications by just substituting some scenario dependent components. In this paper, the authors will explain the general concept and the terrestrial implementation so far. On this basis, the authors will demonstrate and discuss the necessary adaptions to the general concept in order to handle the different conditions on extraterrestrial surfaces.

Smart Drawing for Online Teaching

Teaching and learning-related activities have embraced digital technology especially,with the current global pandemic restrictions pervaded during the last two years.On the other hand,most of the academic and professional presentations are conducted using online platforms.But the presenter-audience interaction is hindered to a certain extent in an online case in contrary to face-to-face where real-time writing is beneficial when sketching is involved.The use of digital pens and pads is a solution for such instances,though the cost of acquiring such hardware is high.Economical solutions are essential as affordability is concerned.In this study,a real-time user-friendly,innovative drawing system is developed to address the issues related to the problems confronted with online presentations.This paper presents the development of an algorithm using Hand Landmark Detection,which replaces chalks,markers and regular ballpoint pens used in conventional communication and presentation,with online platforms.The proposed application in this study is acquired by Python and OpenCV libraries.The letters or the sketches drawn in the air were taken straight to the computer screen by this algorithm.The proposed algorithm continuously identifies the Hand Landmark using the images fed by the web camera,and text or drawing patterns are displayed on the screen according to the movements made by Hand Landmark on the image space.The developed user interface is also user-friendly.Hence the communication of letters and sketches were enabled.Although the concept has been developed and tested,with further research the versatility and accuracy of communication can be enhanced.