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While activity recognition is a current focus of research the challenging problem of fine-grained activity recognition is largely overlooked. We thus propose a novel database of 65 cooking activities, continuously recorded in a realistic setting. Activities are distinguished by fine-grained body motions that have low inter-class variability and high intra-class variability due to diverse subjects...
In this paper, we present a gamesourcing method for automatically and rapidly acquiring labeled images of human poses to obtain ground truth data as input for human pose estimation from 2D images. Typically, these datasets are constructed manually through a tedious process of clicking on joint locations in images. By using a low-cost RGBD sensor, we capture synchronized, registered images, depth maps,...
This paper develops a new constructing approach of an appropriate membership function to integrate a given probability density function and fuzzy Shannon entropy extending the statistical theory into the heuristic method based on the human cognitive behavior and subjectivity. The proposed approach is formulated as a more general mathematical programming problem than previous approaches due to using...
The launch of Xbox Kinect has built a very successful computer vision product and made a big impact to the gaming industry; this sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when faced severe occlusion. In...
In these days, there are many news on stock market on the Internet and investors have to understand them immediately to invest in a stock market. In this study we determine sentimental polarities of the stock market news using a polarity dictionary, which consists of terms and their polarities. To achieve our aim we have to construct the polarity dictionary automatically because of decrease of human...
Muscle force models have many applications in human-machine motion analysis, human-machine interfacing, rehabilitation and robotics. A Hill-type model was used to estimate muscle force. In this work, we are going to introduce a new model to estimate human muscle force. Our model, estimates human muscle force based on a rectified smoothed electromyography (RSEMG) signal using the back-propagation Artificial...
Distance calculation is always one of the most important goals in a digital stereoscopic vision system. In an AER system this goal is very important too, but it cannot be calculated as accurately as we would like. This demonstration shows a first approximation in this field, using a disparity algorithm between both retinas. The system can make a distance approach about a moving object, more specifically,...
Current estimation methods for band level resolutions of human chromosome images in cytogenetic laboratories are time consuming and required experienced specialists to manually perform. To alleviate this problem, in this paper, a computerized approach to estimate band level resolution is proposed. The intensity gradient profile and sign profile of chromosome images are utilized to count the number...
This work presents a robust method for realtime segmentation and tracking of moving objects using depth image sequences, which is insensitive to illumination changes. We propose a novel criterion in our quadtree split-and-merge framework and effectively solves the problem of segmenting objects in complex and cluttered scenes. We also introduce a plane estimation algorithm to cope with the indistinction...
This research presents a 3-D human arms tracking method with a monocular camera. In our previous work, multiple clues have been integrated by the multiple importance sampling particle filter to track the arms with arbitrary motion on the images. Due to the lack of depth information when using a monocular camera, an online sequential pose estimation based on the structure-from-motion is proposed here...
Many methods on extracting 3D information from 2D images have been studied since 1990s, especially the depth information extraction. A novel approach for depth extraction is proposed and implemented in this paper. About 30 images are taken especially for this case study and experiments are conducted on the Stanford Range Image Data. Results show that this approach is generally suitable for most of...
Real-time 3D motion capture for the human hand opens many avenues for HCI. This work describes our framework for fitting a 3D skeleton to the human hand using depth images. We represent a human hand by a 3D skeleton with 15 joints. Using this model, various synthetic depth images are generated. Random Decision Forests (RDF) are trained and used to assign each pixel to a hand part. A mean-shift method...
A novel biometrics approach that performs authentication via the internal non-visible anatomical structure of an individual human eye is proposed and evaluated. To provide authentication, the proposed method estimates the anatomical characteristics of the oculomotor plant (comprising the eye globe, its muscles and the brain's control signals). The estimation of the oculomotor plant characteristics...
In this paper, a new age estimation framework considering the intrinsic properties of human ages is proposed, which improves the dimensionality reduction techniques to learn the connections between facial features and aging labels. To enhance the performance of dimensionality reduction, a distance metric adjustment step is introduced in advance to achieve a suitable metric in the feature space. In...
In this paper, we propose a system to obtain a depth ordered segmentation of a single image based on low level cues. The algorithm first constructs a hierarchical, region-based image representation of the image using a Binary Partition Tree (BPT). During the building process, T-junction depth cues are detected, along with high convex boundaries. When the BPT is built, a suitable segmentation is found...
Body Area Networks is an emerging domain taking a big interest from developers and system designers. On the other hand, the need to localize is becoming necessary in diverse applications. Within this context, the aim of this paper is to estimate the different gestures and motions of the human body. Initially, we use information, about human motion, extracted from C3D files. In fact, these files provide...
When creating a ubiquitous service environment for humans, it is very important to be able to determine their location and movement. In this paper, we propose an algorithm that simultaneously estimates the number of humans and the movement locus for each human in a room, using only the binary sensing data obtained from infrared sensors attached to the ceiling. Compared to other camera-based systems,...
Human age estimation based on face images can figure in a wide variety of real-world applications. In this paper, we propose a novel and efficient facial age estimation algorithm which decides human age in a hierarchical framework. Biologically, human lives can be roughly divided into two stages, the period from birth to adulthood and the period from adulthood to old age, which are quite different...
In some sport training application, it is necessary to search the key frames of training video for carefully analysis. In this paper, we take the key frame searching issue as a pose estimation problem. First, a set of various pose detectors are collected trough the twice SVM training process, each of which can be interpreted as a learned pose-specific HOG weight classifier. Then we run each linear...
The aim of this study is to achieve experimental estimation of whole-body averaged specific absorption rate (WB-SAR) of human models using the radiation-field scanning technique. The original relationship between the WB-SAR and the reference level of ICNIRP Guidelines [1] was obtained through the theoretical analyses using the simple geometrical or block structure. Recently, high resolution numerical...
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