Measurement Function Design for Visual Tracking Applications

Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications

Equivalent standard DEA models to provide super-efficiency scores

DEA super-efficiency models were introduced originally with the objective of providing a tie-breaking procedure for ranking units rated as efficient in conventional DEA models. This objective has been expanded to include sensitivity analysis, outlier identification and inter-temporal analysis. However, not all units rated as efficient in conventional DEA models have feasible solutions in DEA super-efficiency models. We propose a new super-efficiency model that (a) generates the same super-efficiency scores as conventional super-efficiency models for all units having a feasible solution under the latter, and (b) generates a feasible solution for all units not having a feasible solution under the latter. Empirical examples are provided to compare the two super-efficiency models

What sow the seeds of hardship for the poorest of the poor? Towards increasing the performance of informal sector in war affected regions of Sri Lanka

Less performance of informal sector among the poorest of the poor in the war affected regions in Sri Lanka has been caused by many reasons. Findings of an exploratory study and the factor analysis revealed four important factors namely training and skills, education, social and economic. As the extension of the exploratory study, to test this prediction empirically with a larger sample size, the present study applied a survey method using a questionnaire especially designed based on the initial exploratory study which was conducted inductively. A sample of 300 women headed households engaged in the informal sector participated in this study. The results indicates these four factors significantly predict the performance of informal sector. More specifically, while, economic factors contribute more to the performance of the informal sector, training contributes less. The study also discussed the implication of findings and area for future research. Based on the findings and conclusions, few recommendations are also made to enhance the performance of women headed households in the informal sector

Visual Odometry for Quantitative Bronchoscopy Using Optical Flow

Optical Flow, the extraction of motion from a sequence of images or a video stream, has been extensively researched since the late 1970s, but has been applied to the solution of few practical problems. To date, the main applications have been within fields such as robotics, motion compensation in video, and 3D reconstruction. In this paper we present the initial stages of a project to extract valuable information on the size and structure of the lungs using only the visual information provided by a bronchoscope during a typical procedure. The initial implementation provides a realtime estimation of the motion of the bronchoscope through the patients airway, as well as a simple means for the estimation of the cross sectional area of the airway

Tracking with Multiple Cameras for Video Surveillance

The large shape variability and partial occlusions challenge most object detection and tracking methods for nonrigid targets such as pedestrians. Single camera tracking is limited in the scope of its applications because of the limited field of view (FOV) of a camera. This initiates the need for a multiple-camera system for completely monitoring and tracking a target, especially in the presence of occlusion. When the object is viewed with multiple cameras, there is a fair chance that it is not occluded simultaneously in all the cameras. In this paper, we developed a method for the fusion of tracks obtained from two cameras placed at two different positions. First, the object to be tracked is identified on the basis of shape information measured by MPEG-7 ART shape descriptor. After this, single camera tracking is performed by the unscented Kalman filter approach and finally the tracks from the two cameras are fused. A sensor network model is proposed to deal with the situations in which the target moves out of the field of view of a camera and reenters after sometime. Experimental results obtained demonstrate the effectiveness of our proposed scheme for tracking objects under occlusion