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When, in addition to the constant Doppler frequency shift induced by the bulk motion of a radar target, the target or any structure on the target undergoes micro-motion dynamics, such as mechanical vibrations or rotations, the micro-motion dynamics induce Doppler modulations on the returned signal, referred to as the micro-Doppler effect. We introduce the(More)
This paper motivates and describes a novel realization of transductive inference that can address the open set face recognition task. Open set operates under the assumption that not all the test probes have mates in the gallery. It either detects the presence of some biometric signature within the gallery and finds its identity or rejects it, i.e., it(More)
In this paper we study the problem of acquiring a topological model of indoors environment by means of visual sensing and subsequent localization given the model. The resulting model consists of a set of locations and neighborhood relationships between them. Each location in the model is represented by a collection of representative views and their(More)
The localization capability of a mobile robot is central to basic navigation and map building tasks. We describe a probabilistic environment model which facilitates global localization scheme by means of location recognition. In the exploration stage the environment is partitioned into a class of locations, each characterized by a set of scale-invariant(More)
Face recognition performance depends upon the input variability as encountered during biometric data capture including occlusion and disguise. The challenge met in this paper is to expand the scope and utility of biometrics by discarding unwarranted assumptions regarding the completeness and quality of the data captured. Towards that end we propose a(More)
Motivated by recent approaches to object recognition, where objects are represented in terms of parts, we propose a new algorithm for selecting discriminative features based on strangeness measure. We will show that k-nearest neighbour strangeness can be used to measure the uncertainty of individual features with respect to the class labels and forms(More)
The localization capability is central to basic navigation tasks and motivates development of various visual navigation systems. In this paper we describe a two stage approach for localization in indoor environments. In the first stage, the environment is partitioned into several locations, each characterized by a set of scale-invariant keypoints and their(More)
This paper describes a novel application of statistical learning theory (SLT) to single motion estimation and tracking. The problem of motion estimation can be related to statistical model selection, where the goal is to select one (correct) motion model from several possible motion models, given finite noisy samples. SLT, also known as Vapnik-Chervonenkis(More)
Postoperative cognitive dysfunction (POCD) is a significant cause of morbidity after surgery, especially for the elderly. Accumulating evidence has demonstrated that neuroinflammation plays a key role in the pathogenesis of POCD. Thus, we hypothesized that berberine, an isoquinoline alkaloid with anti-inflammatory effects, could improve surgery-induced(More)
This paper describes a novel framework for the Open World face recognition problem, where one has to provide for the Reject option. Based upon algorithmic randomness and transduction, a particular form of induction, we describe the TCM-kNN (Transduction Confidence Machine – kNearest Neighbor) algorithm for Open World face recognition. The algorithm proposed(More)