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We propose a method to derive shading by referring to an unspecified object to synthesize CG objects realistically into an actual scene. Since our method does not require specific light probes and can be implemented with a commercial RGB + depth sensor, it is applicable to consumer environments. The method conducts spherical harmonic (SH) basis functions regression against luminance of the reference...
Varying lighting conditions may cause great face image appearance variance and hence seriously distort the distributions of within and between class distances, but these distributions are exactly the foundation of successful automatic recognition. In this paper, a dynamic illumination distinction description strategy is put forward to compensate for the lighting difference between probe and gallery...
This paper proposes a method for constructing local image descriptors which efficiently encode texture information and are suitable for histogram based representation of image regions. The method computes a binary code for each pixel by linearly projecting local image patches onto a subspace, whose basis vectors are learnt from natural images via independent component analysis, and by binarizing the...
This paper addresses the problem of heterogeneous face recognition where the gallery and probe face samples are captured from two different modalities. Due to large discrepancies yet weak relationships across heterogeneous face image sets, most existing face recognition algorithms usually suffer from this application scenario. To address this problem, we propose in this paper to learn modality-invariant...
We present a real-time 3D face identification system using a consumer level depth camera (PrimeSensor). Our system takes a noisy sequence as input and produces reliable identification. Instead of registering a probe to all instances in the database, we propose to only register it with several intermediate references, which considerably reduces processing, while preserving the recognition rate. The...
In this paper, we introduce a torus manifold-based temporal super resolution method for gait recognition from low frame-rate videos with view transitions. Given a low frame-rate gait sequence with view transition from an unknown person, we estimate three unknowns: view, phase, and style. We estimate view by walking trajectory and camera information, phase by dynamic programming using multiview exemplar...
As a new biometric for person authentication, hand-dorsa vein has attracted increasing attention in recent years. This paper proposes a novel approach for hand-dorsa vein recognition, which makes use of multi-level keypoint detection and SIFT feature based local matching. In order to overcome the difficulty in finding local features on NIR images of hand dorsa, a multi-level keypoint detection approach,...
Recognizing faces in surveillance videos becomes difficult due to the poor quality of the probe data in terms of resolution, noise, blurriness, and varying lighting conditions. In addition, the poses of probe data are usually not frontal view, contrary to the standard format of the gallery data. The discrepancy between the two types of the data makes the existing recognition algorithm less accurate...
In gait recognition field, template-based approaches such as Gait Energy Image (GEI) and Chrono-Gait Image (CGI) can achieve good recognition performance with low computational cost. Meanwhile, CGI can preserve temporal information better than GEI. However, they pay less attention to the local shape features. To preserve temporal information and generate more abundant local shape features, we generate...
Microarrays are massively parallel biosensors that can simultaneously detect and quantify a large number of different genomic particles. A DNA microarray is a nucleic acid-based microarray that contains probe spots testing a multitude of targets in one experiment. Ideas from compressive sensing have been utilized in different ways in the analysis of DNA microarrays. One of the proposed methods is...
Gait recognition performance is often degraded by intra-subject gait fluctuations such as temporal fluctuations due to non-uniform evolution of phase (gait stance) and spatial fluctuations in arm swings or posture within the same phase. Therefore, we first propose a method for gait recognition using a phase-normalized image sequence to overcome the temporal fluctuations. However, it has been noticed...
This paper delves into the effectiveness of a gait recognition process depending on the length of the video sequence used. To this end, a well-known gait representation, the Gait Energy Image (GEI), is incrementally computed from gait cycles in the order they occur. The main objective is to assess the problem of the minimum number of gait cycles required to obtain discriminant GEIs. An experimental...
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