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Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper , we present one of the first studies on unsupervised domain adaptation in the context of object recognition, where we have labeled data only from the source domain (and therefore do not(More)
As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past several years. At least two reasons account for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible(More)
The discrimination power of various human facial features is studied and a new scheme for automatic face recognition (AFR) is proposed. The first part of the paper focuses on the linear discriminant analysis (LDA) of different aspects of human faces in the spatial as well as in the wavelet domain. This analysis allows objective evaluation of the(More)
Several recently developed techniques for reconstructing surface shape from shading information estimate surface slopes without ensuring that they are integrable. This paper presents a n approach for enforcing integrability, a particular implementation of the approach , a n example of its application to extending a n existing shape-from-shading algorithm,(More)
A robust approach to recovery of shape from shading information is presented. Assuming uniform albe-do and Lambertian surface for the imaging model, we first present methods for the estimation of illuminant direction and surface albedo. The illuminant azimuth is estimated by averaging local estimates. The illumi-nant elevation and surface albedo are(More)
We propose a new objective function for superpixel seg-mentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term. The entropy rate favors formation of compact and homogeneous clusters, while the balancing function encourages clusters with similar sizes. We present a novel graph construction(More)
— The past decade has witnessed a rapid proliferation of video cameras in all walks of life and has resulted in a tremendous explosion of video content. Several applications such as content-based video annotation and retrieval, highlight extraction and video summarization require recognition of the activities occurring in the video. The analysis of human(More)
Recently introduced cost-effective depth sensors coupled with the real-time skeleton estimation algorithm of Shotton et al. [16] have generated a renewed interest in skeleton-based human action recognition. Most of the existing skeleton-based approaches use either the joint locations or the joint angles to represent a human skeleton. In this paper, we(More)
In this paper we describe a face recognition method based on PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis). The method consists of two steps: rst we project the face image from the original vector space to a face subspace via PCA, second we use LDA to obtain a best linear clas-siier. The basic idea of combining PCA and LDA is to(More)
We propose a view-based approach to recognize humans from their gait. Two different image features have been considered: the width of the outer contour of the binarized silhouette of the walking person and the entire binary silhouette itself. To obtain the observation vector from the image features, we employ two different methods. In the first method,(More)