|
T. Alejandra Vidal, Andrew J. Davison, Juan Andrade, & David W. Murray. (2006). Active Control for Single Camera SLAM.
|
|
|
T. Alejandra Vidal, A. Sanfeliu, & Juan Andrade. (2006). Autonomous Single Camera Exploration.
|
|
|
Fadi Dornaika, & Franck Davoine. (2006). Facial expression recognition using auto-regressive models.
|
|
|
R. Herault, Franck Davoine, Fadi Dornaika, & Y. Grandvalet. (2006). Simultaneous and robust face and facial action tracking.
|
|
|
Ignasi Rius, Javier Varona, Jordi Gonzalez, & Juan J. Villanueva. (2006). Action Spaces for Efficient Bayesian Tracking of Human Motion.
|
|
|
Lubomir Latchev, Maya Dimitrova, & David Rotger. (2006). A Classifier of Technical Diagnostic States of Electrocardiograph.
|
|
|
Dani Rowe. (2008). Towards Robust Multiple-Target Tracking in Unconstrained Human-Populated Environments.
|
|
|
Carme Julia. (2008). Missig Data Matrix Factorization Addressing the Structure from Motion Problem.
|
|
|
Francesco Ciompi. (2008). ECOC-based Plaque Classification using In-vivo and Exvivo Intravascular Ultrasound Data.
|
|
|
Pierluigi Casale. (2008). Social Environment Description from Data Collected with a Wearable Device.
|
|
|
Jon Almazan, Bojana Gajic, Naila Murray, & Diane Larlus. (2018). Re-ID done right: towards good practices for person re-identification.
Abstract: Training a deep architecture using a ranking loss has become standard for the person re-identification task. Increasingly, these deep architectures include additional components that leverage part detections, attribute predictions, pose estimators and other auxiliary information, in order to more effectively localize and align discriminative image regions. In this paper we adopt a different approach and carefully design each component of a simple deep architecture and, critically, the strategy for training it effectively for person re-identification. We extensively evaluate each design choice, leading to a list of good practices for person re-identification. By following these practices, our approach outperforms the state of the art, including more complex methods with auxiliary components, by large margins on four benchmark datasets. We also provide a qualitative analysis of our trained representation which indicates that, while compact, it is able to capture information from localized and discriminative regions, in a manner akin to an implicit attention mechanism.
|
|
|
A. Pujol, Felipe Lumbreras, Javier Varona, & Juan J. Villanueva. (1999). Template matching through invariant eigenspace projection..
|
|
|
Antonio Lopez, David Lloret, & Joan Serrat. (1998). Creaseness measures for CT and MR image registration..
Abstract: Creases are a type of ridge/valley structures that can be characterized by local conditions. Therefore, creaseness refers to local ridgeness and valleyness. The curvature K of the level curves and the mean curvature kM of the level surfaces are good measures of creaseness for 2-d and 3-d images, respectively. However, the way they are computed gives rise to discontinuities, reducing their usefulness in many applications. We propose a new creaseness measure, based on these curvatures, that avoids the discontinuities. We demonstrate its usefulness in the registration of CT and MR brain volumes, from the same patient, by searching the maximum in the correlation of their creaseness responses (ridgeness from the CT and valleyness from the MR). Due to the high dimensionality of the space of transforms, the search is performed by a hierarchical approach combined with an optimization method at each level of the hierarchy
|
|
|
Antonio Lopez, Felipe Lumbreras, & Joan Serrat. (1998). Creaseness form level set extrinsec curvature..
|
|
|
Antonio Lopez, Ricardo Toledo, Joan Serrat, & Juan J. Villanueva. (1999). Extraction of vessel centerlines from 2D coronary angiographies.
|
|