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This paper presents a subject centric group feature for person re-identification. Our approach is inspired by the observation that people often tend to walk alongside others or in a group. We argue that co-travelers' information, including geometry and visual cues, can reduce the re-identification ambiguity and lead to better accuracy, compared to approaches that rely only on visual cues. We introduce...
3D-Model-Aided 2D face recognition (MaFR) has attracted a lot of attention in recent years. By registering a 3D model, facial textures of the gallery and the probe can be lifted and aligned in a common space, thus alleviating the challenge of pose variations. One obstacle preventing accurate registration is the 3D-2D pose estimation, which is easily affected by landmarks. In this work, we present...
In this paper, we demonstrate the effectiveness of using statistical shape priors to recover shape descriptors from occluded objects in a level set based variational framework. Parameters that balance curve evolution forces are estimated systematically through embedded discrete Conditional Random Field (CRF). In addition, our approach exploits the benefit of using spectral data to construct a local...
Cell segmentation is a challenging problem in histology and cytology that can benefit from additional information obtained in using multispectral imaging. Unique transmission spectra of biological tissues are potentially useful for better classification and segmentation of sub-cellular structures. In this paper, we propose a conditional random field (CRF) model that interprets high-dimensional spectral...
In this paper we propose fast face recognition system based on the Kekre's transform. This algorithm can be easily implemented and number of coefficients required for recognition reduces drastically compared to benchmark algorithm PCA. Thus computational burden decreases. We have compared the performance of this transform with conventional transforms like DCT, DST, Slant transform and WHT. The algorithm...
Multispectral microscopy for applications in histology and cytology has shown that the unique transmission spectra of biological tissue provides additional information that is potentially useful for better classification and segmentation of sub-cellular structures. In this paper, we propose a conditional random field (CRF) model that incorporates spectral data during inference for the problem of segmenting...
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