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In this paper we address robot-human interactions in a multi-robot and people group framework. The objective is to develop and evaluate techniques for missions in which several robots cooperate among themselves, interacting with a group of people. The robots detect people behaviors and act consequently adopting different strategies. Probabilistic techniques for robust cooperative detection of group...
We propose a human motion tracking method for fast motion clips using synchronized multiple cameras. Our method is capable of extracting 3D articulated postures with 42 degrees of freedom through a sequence of visual hulls. We seek for the globally optimal solutions of the likelihood with the local memorization about the “fitness” of each body segment. Our method avoids the local minimum problem efficiently...
In this paper we introduce the WR (Workflow Recognition) dataset. Recorded in the production line of a major automobile manufacturer, this dataset consists of sequences that depict workers executing industrial workflows. The heavy occlusions, outliers, the visually complicated background and the human-machinery interaction are among the factors that make this dataset a very challenging testbed for...
In this paper, we propose a cost function approach for multi-human tracking. We first build short reliable trajectories based on human appearance and position. Here, we apply topic model to represent human appearance. The appearance of each person can be considered as topic distribution. Then, we compute the cost function for each pair of reliable trajectories in the time sliding window to estimate...
This paper presents a completely unsupervised mechanism for learning micro-actions in continuous video streams. Unlike other works, our method requires no prior knowledge of an expected number of labels (classes), requires no silhouette extraction, is tolerant to minor tracking errors and jitter, and can operate at near real time speed. We show how to construct a set of training “tracklets,” how to...
The main contribution of this paper is a new people detection algorithm based on motion information. The algorithm builds a people motion model based on the Implicit Shape Model (ISM) Framework and the MoSIFT descriptor. We also propose a detection system that integrates appearance, motion and tracking information. Experimental results over sequences extracted from the TRECVID dataset show that our...
Most work on activity recognition focuses on 2D image properties, holistic spatiotemporal representations, or space-time shapes in image domain rather than with 3D pose in a body-centric or world frame. Such techniques rely on advanced pattern recognition algorithms and interpreting complex behavioral patterns. In this work we posit that it is possible to achieve 3D pose tracking using videos recorded...
Throughout the day, the human visual system acquires information using saccade and vergence eye movements. Previously, functional MRI (fMRI) experiments have shown both shared neural resources and spatial differentiation between these two systems. FMRI experiments can reveal which regions are activated within an experimental task but do not yield insight into how regions of interest (ROIs) interact...
Information technology currently supports the development of human interaction with virtual environment, this development will continue in developing in the form of Human Computer Interaction (HCI). In this study, how the environment 3D virtual computer should be able to recognize human hand as part as virtual object, so it can interact with virtual environment.
Human action recognition is gaining interest from many computer vision researchers because of its wide variety of potential applications. For instance: surveillance, advanced human computer interaction, content-based video retrieval, or athletic performance analysis. In this research, we focus to recognize some human actions such as waving, punching, clapping, etc. We choose exemplar-based sequential...
A crucial challenge in human body tracking is the high degrees of freedom (up to around 40) to be recovered. A method based on multi-objective optimization algorithm is presented here to tackle this problem. In our multi-objective optimization based human body tracking framework, tracking is considered as two functions' co-optimization problem where the aim is to optimize the matching functions between...
In this paper we propose a method for pupil localizing in infrared video images. Pupil localizing is the first step toward eye monitoring. The proposed method is based on three phases. At first the pupil is segmented. Pupil segmentation is based on thresholding. The threshold value is estimated on the basis of a genetic algorithm using Otsu thresholding technique. Following, the pupil is modeled....
In driver assistance system, human eye gaze direction is an important feature described some driver's situation such as distraction and fatigue. This paper proposes a method to track driver's gaze direction by using deformable template matching. The method is divided into three steps: first, identifying the face area. Second, localizing the eye area. Finally, combining the eye region model and sight...
In this paper, a human detection and tracking system in a crowded environment is presented. The biggest challenge of the system is to detect occluded people from the captured video where visible information of the occluded people in a camera is reduced. Many researchers proposed to reconstruct the occluded information from other cameras which are installed in the same place with different viewing...
Analysis of motion patterns is an effective approach for gaining better understanding of human behaviour. Many methods have been proposed to tackle this problem. However, unsupervised approaches have been widely accepted for clustering motion patterns, due to the fact that no previous knowledge of the scene is required. The fuzzy self-organizing map (fuzzy SOM) is an unsupervised method which has...
The articulated body tracking is challenging area in HCI (Human Computer Interaction) community. In this paper, we propose a method for robust articulated body tracker using dense disparity maps, which reduce the searching space, derived from stereo image sequences. To track an articulated body we first model the human body as MRF networks with tree structured graph, and belief propagation(BP) is...
An upper limb stroke rehabilitation system is developed which combines electrical stimulation with mechanical arm support, to assist patients performing 3D reaching tasks in a virtual reality environment. The Stimulation Assistance through Iterative Learning (SAIL) platform applies electrical stimulation to two muscles in the arm using model-based control schemes which learn from previous trials of...
The main objective of this paper is to design and develop a novel hybrid human motion tracking system for gait and dynamic balance training program based on virtual reality games for children with motor impairments. The whole training program comprises of a novel human motion tracking system and a VR game system that enables objective monitoring of a child's progress, improves consistency between...
Human Motion Capture (HMC) is an active topic of research with applications in diverse domains. The robotics community is in particular interested in methods which allow the tracking of human movements on autonomous robotic systems with their constrained perception and processing capabilities. One approach for such a tracking is based on the Iterative Closest Points (ICP) algorithm. A specific problem...
In this paper we propose a novel approach for interactive manipulation involving a human and a humanoid. The interaction is represented by means of the relative configuration between the human's and the robot's hands. Based on this principle and a set of mathematical tools also proposed in the paper, a large set of tasks can be represented intuitively. We also introduce the concept of simultaneous...
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