Prototype-based budget maintenance for tracking in depth videos

© 2016, Springer Science+Business Media New York. The use of conventional video tracking based on color or gray-level videos often raises concerns about the privacy of the tracked targets. To alleviate this issue, this paper presents a novel tracker that operates solely from depth data. The proposed tracker is designed as an extension of the popular Struck algorithm which leverages the effective framework of structural SVM. The main contributions of our paper are: i) a dedicated depth feature based on local depth patterns, ii) a heuristic for handling view occlusions in depth frames, and iii) a technique for keeping the number of the support vectors within a given “budget” so as to limit computational costs. Experimental results over the challenging Princeton Tracking Benchmark (PTB) dataset report a remarkable accuracy compared to the original Struck tracker and other state-of-the-art trackers using depth and RGB data

Local depth patterns for fine-grained activity recognition in depth videos

© 2016 IEEE. Fine-grained activities are human activities involving small objects and small movements. Automatic recognition of such activities can prove useful for many applications, including detailed diarization of meetings and training sessions, assistive human-computer interaction and robotics interfaces. Existing approaches to fine-grained activity recognition typically leverage the combined use of multiple sensors including cameras, RFID tags, gyroscopes and accelerometers borne by the monitored people and target objects. Although effective, the downside of these solutions is that they require minute instrumentation of the environment that is intrusive and hard to scale. To this end, this paper investigates fine-grained activity recognition in a kitchen setting by solely using a depth camera. The primary contribution of this work is an aggregated depth descriptor that effectively captures the shape of the objects and the actors. Experimental results over the challenging '50 Salads' dataset of kitchen activities show an accuracy comparable to that of a state-of-the-art approach based on multiple sensors, thereby validating a less intrusive and more practical way of monitoring fine-grained activities

Joint action recognition and summarization by sub-modular inference

© 2016 IEEE. Action recognition and video summarization are two important multimedia tasks that are useful for applications such as video indexing and retrieval, video surveillance, humancomputer interaction and home intelligence. While many approaches exist in the literature for these two tasks, to date they have always been addressed separately. Instead, in this paper we move from the assumption that these two tasks should be tackled as a joint objective: on the one hand, action recognition can drive the selection of meaningful and informative summaries; on the other, recognizing actions from a summary rather than the entire video can in principle reduce noise and prove more accurate. To this aim, we propose a novel approach for joint action recognition-summarization based on the performing latent structural SVM framework, together with an efficient algorithm for inferring the action and the summary based on the property of sub-modularity. Experimental results on a challenging benchmark, MSR Dai-lyActivity3D, show that the approach is capable of achieving remarkable action recognition accuracy while providing appealing video summaries

The use of privacy-protected computer vision to measure the quality of healthcare worker hand hygiene

© 2018 The Author(s). Objectives: (i) To demonstrate the feasibility of automated, direct observation and collection of hand hygiene data, (ii) to develop computer visual methods capable of reporting compliance with moment 1 (the performance of hand hygiene before touching a patient) and (iii) to report the diagnostic accuracy of automated, direct observation of moment 1. Design: Observation of simulated hand hygiene encounters between a healthcare worker and a patient. Setting: Computer laboratory in a university. Participants: Healthy volunteers. Main outcome measures: Sensitivity and specificity of automatic detection of the first moment of hand hygiene. Methods: We captured video and depth images using a Kinect camera and developed computer visual methods to automatically detect the use of alcohol-based hand rub (ABHR), rubbing together of hands and subsequent contact of the patient by the healthcare worker using depth imagery. Results: We acquired images from 18 different simulated hand hygiene encounters where the healthcare worker complied with the first moment of hand hygiene, and 8 encounters where they did not. The diagnostic accuracy of determining that ABHR was dispensed and that the patient was touched was excellent (sensitivity 100%, specificity 100%). The diagnostic accuracy of determining that the hands were rubbed together after dispensing ABHR was good (sensitivity 83%, specificity 88%). Conclusions: We have demonstrated that it is possible to automate the direct observation of hand hygiene performance in a simulated clinical setting. We used cheap, widely available consumer technology and depth imagery which potentially increases clinical application and decreases privacy concerns

Accomplishes Foreign Direct Investment Affect Private Investment In Arab Nations In The Period Between (2000 – 2021)?

The article desires to examine the impact of FDI on PI with a sampling of 10 selected Arab countries from 2000- 2021. For further analysis, the study used OLS. Test method with fixed and random effects model, and after making Haussmanns test and accepting the Alternative Hypothesis (H1), the study used the fixed effects model. The results confirm the presence of crowding in reality, which indicates that FDI encourages PI in only one model. Aside from this, the delayed PI has a positive and essential impact on herself in the coming period reflecting stagnation in the direction of PI in the beneficiary nations. In the complete panel sample, thither is a significant negative effect between inflation and PI, there are some macro elements that as per capita GDP, electro, domestic credit, and labor force, which were positive and not statistically significant, while trade openness was negative and not statistically significant

Tautomerism of 5-methyl imidazolidine thio derivatives in the gas phase: a density functional study

Relative tautomerisation energies, enthalpies, entropies, Gibbs free energies, and dipole moments for 5-methyl-2,4-dioxo-imidazolidine and its thio analogous have been studied in the gas phase using hybrid density functional at the B3LYP level of theory using 6-31(d) and 6-31

ASSESSING ONLINE REGISTRATION SYSTEM’S (ORS) SUCCESS: AN APPLICATION OF DELONE AND MCLEAN’S MODEL OF INFORMATION SYSTEMS SUCCESS

The study applied DeLone and McLean’s IS success model in the mandatory context of online registration system (ORS) in one Jordanian university. Six dimensions were used to asses ORS success from the perspective of system users, i.e. students (information quality, system quality, service quality, user satisfaction, net benefits and intention to use). Consistent with DeLone and McLean’s suggestion, the study focused on the “intention to use”, rather than “use”, dimension to accommodate the mandatory nature of ORS. Quantitative data was collected, through a questionnaire instrument, from a sample of 1360 undergraduate students studying in different faculties at the university. Statistical analysis of the study’s model was conducted using “SmartPLS” software, version 2.0.M3. Empirical analysis has underlined the multidimensional and interdependent nature of ORS success. Furthermore, empirical examination of the model’s hypotheses has indicated that students’ “intention to use” ORS is dependent on system quality, service quality, user satisfaction and net benefits