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Titlebook: Computer Vision - ECCV 2008; 10th European Confer David Forsyth,Philip Torr,Andrew Zisserman Conference proceedings 2008 Springer-Verlag Be

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Scale Invariant Action Recognition Using Compound Features Mined from Dense Spatio-temporal Cornersneered” to be both sparse and invariant to transformation and it is assumed that they provide the greatest discriminative information. To tackle activity recognition, we propose learning compound features that are assembled from simple 2D corners in both space and time. Each corner is encoded in rel
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Semi-supervised On-Line Boosting for Robust Trackingcurrent view of the object from its surrounding background needs to be discriminiated. However, on-line adaption faces one key problem: Each update of the tracker may introduce an error which, finally, can lead to tracking failure (drifting). The contribution of this paper is a novel on-line semi-su
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234146.jpg
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https://doi.org/10.1007/978-3-540-88682-2action recognition; aerial imagery; algorithms; edge detection; motion capture; multi body tracking; multi
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Advances in Cryptology – EUROCRYPT 2023rk in cybernetics, psychology, physics, mathematics and philosophy) till my retirement earlier this year (hence the slightly blue feeling), thus my career roughly covers the history of the field. “Vision” has diverse connotations. The fundamental dichotomy is between “optically guided action” and “v
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Pratish Datta,Ilan Komargodski,Brent Waters a way that is not specific to the localization task. First a binary classifier is trained using a sample of positive and negative examples, and this classifier is subsequently applied to multiple regions within test images. We propose instead to treat object localization in a principled way by posi
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