Making sense of hand gestures in applications such as novel user interfaces is an active area of research. Many current methods use complex 3D model of non-rigid hands and involved paradigms in solving the general pro...
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Human gait and activity analysis from video is presently attracting a lot of attention in the computervision community, In this paper, we analyze the role of two of the most important cues in human motion- shape and ...
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Human gait and activity analysis from video is presently attracting a lot of attention in the computervision community, In this paper, we analyze the role of two of the most important cues in human motion- shape and kinematics. We present an experimental framework whereby it is possible to evaluate the relative importance of these two cues in computervision based recognition algorithms. In the process, we propose a new gait recognition algorithm by computing the distance between two sequences of shapes that lie on a spherical manifold. In our experiments, shape is represented using Kendall's definition of shape. Kinematics is represented using a Linear Dynamical system. We place particular emphasis on human gait. Our conclusions show that shape plays a role which is more significant than kinematics in current automated gait based human identification algorithms. As a natural extension we study the role of shape and kinematics in activity recognition. Our experiments indicate that we require models that contain both shape and kinematics in order to perform accurate activity classification. These conclusions also allow us to explain the relative performance of many existing methods in computer-based human activity modeling.
This paper presents a system for inferring complex mental states from video of facial expressions and head gestures in real-time. The system is based on a multi-level dynamic Bayesian network classifier which models c...
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Traditionally, the problem of stereo matching has been addressed either by a local window-based approach or a dense pixel-based approach using global optimization. In this paper, we present an algorithm which combines...
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Traditionally, the problem of stereo matching has been addressed either by a local window-based approach or a dense pixel-based approach using global optimization. In this paper, we present an algorithm which combines window-based local matching into a global optimization framework. Our local matching algorithm assumes that local windows can have at most two disparities. Under this assumption, the local matching can be performed very efficiently using graph cuts. The global matching is formulated as minimization of an energy term that takes into account the matching constraints induced by the local stereo algorithm. Fast, approximate minimization of this energy is achieved through graph cuts. The key feature of our algorithm is that it preserves discontinuities both during the local as well as global matching phase.
Previous research has established thermal infrared imagery of faces as a valid biometric and has shown high recognition performance in a wide range of scenarios. However, all these results have been obtained using eye...
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Given an image, how do we automatically assign keywords to it? In this paper, we propose a novel, graph-based approach (GCap) which outperforms previously reported methods for automatic image captioning. Moreover, it ...
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In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shape-from-silhouette or visual-hull systems, as no additional data is needed fo...
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In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shape-from-silhouette or visual-hull systems, as no additional data is needed for calibration. The hey novel contribution of this work is an algorithm to robustly compute the epipolar geometry from dynamic silhouettes. We use the fundamental matrices computed by this method to determine the protective reconstruction of the complete camera configuration. This is refined into a metric reconstruction using self-calibration. We validate our approach by calibrating a four camera visual-hull system from archive data where the dynamic object is a moving person. Once the calibration parameters have been computed, we use a visual-hull algorithm to reconstruct the dynamic object from its silhouettes.
Automatic image orientation detection for natural images is a useful, yet challenging research area. Humans use scene context and semantic object recognition to identify the correct image orientation. However, it is d...
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This paper is concerned with the theory of non-rigid registration and image warping. Our approach combines the Brownian warps model proposed by Nielsen et al. with the differential operator approach proposed by Joshi ...
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A key step for the effective use of local image features (i.e., highly distinctive and robust features) for recognition or image matching is the appropriate grouping of feature matches. Spatial constraints are importa...
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A key step for the effective use of local image features (i.e., highly distinctive and robust features) for recognition or image matching is the appropriate grouping of feature matches. Spatial constraints are important in this grouping because, during a recognition process, they allow for the reduction of the number of hypotheses that must be verified and also reduce the number of false positives present in each of these hypotheses. A common choice for this grouping task is to use the Hough transform on the global spatial transformation parameters of the hypothesized matches. Here, instead, we use semi-local spatial constraints which allow for a greater range of shape deformations. A comparison with Hough transform shows that our method is more robust to both rigid and non-rigid deformations. Its functionality is demonstrated in an exemplar-based object recognition system that deals well with severe non-rigid deformations. We also show the efficacy of our flexible spatial grouping for long range motion problems.
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