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In this paper we introduce a framework for automated text recognition from images. We first describe a simple but efficient text detection and recognition method based on analysis of maximally stable extremal regions (MSERs) and simple template matching which allows to provide initial character recognition results. The main emphasis of the paper is on introducing a novel method for exploiting contextual...
This paper demonstrates how to reduce the hand labeling effort considerably by 3D information in an object detection task. In particular, we demonstrate how an efficient car detector for aerial images with minimal hand labeling effort can be build. We use an on-line boosting algorithm to incrementally improve the detection results. Initially, we train the classifier with a single positive (car) example,...
Object reacquisition or reidentification is the process of matching objects between images taken from separate cameras. In this paper, we present our work on feature based object reidentification performed on autonomous embedded smart cameras and applied to traffic scenarios. We present a novel approach based on PCA-SIFT features and a vocabulary tree. By building unique object signatures from visual...
Recent results on stereo indicate that an accurate segmentation is crucial for obtaining faithful depth maps. Variational methods have successfully been applied to both image segmentation and computational stereo. In this paper we propose a combination in a unified framework. In particular, we use a Mumford-Shah-like functional to compute a piecewise smooth depth map of a stereo pair. Our approach...
In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional signals. We first use CCA to perform 3D face reconstruction and in a separate application we predict near-infrared (NIR) face texture. In both cases, the input data are color (RGB) face...
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