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Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage...
In this paper, we propose a new local descriptor based on the approximate radial gradient transform. Initially, the interest points are detected using the difference of box filters. Then, the circular region of certain size around these interest points is represented using the approximate radial gradient transform and hence the descriptor is formed. We have conducted experiments on some of the well...
A face recognition algorithm based on a newly developed Transform Domain Modular (TDM) approach is proposed. In this approach, the spatial faces are divided into smaller sub-images, which are processed using non-overlapping and overlapping windows. Each image is subsequently transformed using a compressing transform such as the two dimensional discrete cosine transform. This produces the TDM-2D and...
Performance of face recognition system has not been satisfied due to the change of illumination on facial image. Thus, there were many proposals that dealing with illumination compensation in face recognition in the past decades. In this paper, we propose a wavelet based illumination invariant algorithm based on the illumination-reflectance model. The proposed method aims to remove illumination component...
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