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The proof of human parts has an imperative effect on pose evaluation, and can be effortlessly confused with difficult background due to indefinite part detector. This paper circumvents this predicament by performing a proof supporting approach, where each part also receives confidence from its neighborhood which uses the outline information between connect parts and mitigates the risk of being blindly...
Many approaches have been proposed for human pose estimation in single and multi-view RGB images. However, some environments, such as the operating room, are still very challenging for state-of-the-art RGB methods. In this paper, we propose an approach for multi-view 3D human pose estimation from RGB-D images and demonstrate the benefits of using the additional depth channel for pose refinement beyond...
We propose a new method for human pose estimation from a single image. Since both appearance and locations of different body parts strongly depends on each other in an image, considering their relationship helps identifying the underlying poses. However, most of the existing methods cannot fully utilize this contextual information by using simplified model to make inference tractable. The proposed...
We propose a novel framework for searching for people in surveillance environments. Rather than relying on face recognition technology, which is known to be sensitive to typical surveillance conditions such as lighting changes, face pose variation, and low-resolution imagery, we approach the problem in a different way: we search for people based on a parsing of human parts and their attributes, including...
We address the problem of articulated 2-D human pose estimation in unconstrained natural images. In previous work the Pictorial Structure Model approach has proven particularly successful, and is appealing because of its moderate computational cost. However, the accuracy of resulting pose estimates has been limited by the use of simple representations of limb appearance. We propose strong discriminatively...
In this paper, a framework for validating any generic face detection algorithm's result is proposed. A two stage cascaded face validation filter is described that relies on a skin-color detector and on a face silhouette structure modeler towards increasing face detection capacity of any face detection algorithm. While the skin-color detector combines a static skin-color and a dynamic background-color...
This paper extends the face detection framework proposed by Viola and Jones to handle all upright face poses between full left and full right profiles and also describes its combination with Camshift based face tracking system. The whole 180deg degree range was divided into 5 sub-ranges and their corresponding view based detectors are constructed separately. Face detection framework is a combination...
This paper addresses the problem of recovering 3D human pose from a single monocular image. In the literature, Bayesian Mixtures of Experts (BME) was successfully used to represent the multimodal image-to-pose distributions. However, the expectation-maximization (EM) algorithm that learns the BME model may converge to a suboptimal local maximum. And the quality of the final solution depends largely...
The objective of this paper is to estimate 2D human pose as a spatial configuration of body parts in TV and movie video shots. Such video material is uncontrolled and extremely challenging. We propose an approach that progressively reduces the search space for body parts, to greatly improve the chances that pose estimation will succeed. This involves two contributions: (i) a generic detector using...
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