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Multimodal classification arises in many computer vision tasks such as object classification and image retrieval. The idea is to utilize multiple sources (modalities) measuring the same instance to improve the overall performance compared to using a single source (modality). The varying characteristics exhibited by multiple modalities make it necessary to simultaneously learn the corresponding metrics...
In this paper, a part-based technique for real time detection of users' faces on mobile devices is proposed. This method is specifically designed for detecting partially cropped and occluded faces captured using a smartphone's front-facing camera for continuous authentication. The key idea is to detect facial segments in the frame and cluster the results to obtain the region which is most likely to...
Fasteners are critical railway components that maintain the rails in a fixed position. Their failure can lead to train derailments due to gage widening or wheel climb, so their condition needs to be periodically monitored. Several computer vision methods have been proposed in the literature for track inspection applications. However, these methods are not robust to clutter and background noise present...
In this paper, we propose an automatic method for determining the head pose from a given face image. The face image is divided into a regular grid and a representation of the image is obtained by extracting dense SIFT descriptors from its grid points. Random Projection (RP) is then applied to reduce the dimension of the concatenated SIFT descriptor vector. Classification and regression using Support...
We consider the problem of automatic age estimation from face images. Age estimation is usually formulated as a regression problem relating the facial features and the age variable, and a single regression model is learnt for all ages. We propose a hierarchical approach, where we first divide the face images into various age groups and then learn a separate regression model for each group. Given a...
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