Abstract: We address the problem of learning an adaptive appearance model for object tracking. In particular, a class of tracking techniques called ``tracking by detection'' have been shown to give promising results at real-time speeds. These methods train a discriminative classifier in an online manner to separate the object from the background. This classifier bootstraps itself by using the current tracker state to extract positive and negative examples from the current frame. Slight inaccuracies in the tracker can therefore lead to incorrectly labeled training examples, which degrades the classifier and can cause further drift. In this work, we show that using Multiple Instance Learning (MIL) instead of traditional supervised learning avoids these problems, and can therefore lead to a more robust tracker with fewer parameter tweaks. We present a novel online MIL algorithm for object tracking that achieves superior results with real-time performance. Bio: Ming-Hsuan Yang is an assistant professor in Electrical Engineering and Computer Science of University of California at Merced. Â After receiving his PhD degree in Computer Science from the University of Illinois at Urbana-Champaign (UIUC), he worked as a senior researcher at the Honda Research Institute in Mountain View, California, and was an assistant professor with Computer Science and Information Engineering at National Taiwan University. His research interests include computer vision, pattern recognition, robotics, cognitive science, and machine learning. While at UIUC, he was awarded the Ray Ozzie Fellowship given to outstanding graduate students in Computer Science. He has co-authored the book Face Detection and Gesture Recognition for Human-Computer Interaction (Kluwer Academic Publishers), and co-edited a special issue on face recognition of Computer Vision and Image Understanding. He serves as an Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence, and Image and Vision Computing. He serves on several conferences, including Area Chair of the IEEE Computer Vision and Pattern Recognition in 2008 and 2009, publication chair in 2010, and Area Chair of Asian Conference on Computer Vision in 2009 and 2010. He is a senior member of the IEEE and the ACM. Note: Please contact me via email (firstname.lastname@example.org) if you are interested in working with me as I may take one or two students/postdocs.