Sharif Digital Repository

To date various commercial systems have been used in the GAIT analysis. These systems have some difficulties for clinical use, such as interfering with normal movement and high prices. The possibility of utilization of Kinect as a sensor for GAIT analysis has been studied in this research. The accuracy of Kinect in calculation of GAIT parameters such as lower limb joint angles, stride time, and stride length were computed during normal walking. The effects of the sensor's position and direction relative to the walkway were also investigated. The Kinect sensor was installed at different positions toward the motion path. In each position the data was recorded by both Kinect and a commercial... 

Motion capture systems are used to gauge the kinematic features of the motion in numerous fields of research. Despite superb accuracy performance, the commercial systems are costly and difficult to use. To solve these issues, Kinect has been proposed as a low-priced markerless motion capture sensor, and its accuracy has been assessed using previous motion capture systems. However, in many of these studies, the anatomical joint angles captured using the Kinect are compared to the 3D rotation angles reported by the gold standard motion capture systems. These incompatibilities in the determination of the human joint angles can lead to higher error estimation. To accomplish a valid accuracy... 

Semantic segmentation is one of the most important tasks in the field of computer vision. It is the main step towards scene understanding. With the advent of RGB-Depth sensors, such as Microsoft Kinect, nowadays RGB-Depth images are easily available. This has changed the landscape of some tasks such as semantic segmentation. As the depth images are independent of illumination, the combination of depth and RGB images can improve the quality of semantic labeling. The related research has been divided into two main categories, based on the usage of hand-crafted features and deep learning. Although the state-of-the-art results are mainly achieved by deep learning methods, traditional methods... 

Evaluation of workers’ body posture in workstations is a prerequisite to estimate spinal loads and assess risk of injury for the subsequent design of preventive interventions. The Microsoft Kinect™ sensor is, in this regard, advantageous over the traditional skin-marker-based optical motion capture systems for being marker-less, portable, cost-effective, and easy-to-use in real workplaces. While several studies have demonstrated the validity/reliability of the Kinect for posture measurements especially during gait trials, its capability to adequately drive a detailed spine musculoskeletal model for injury risk assessments remains to be investigated. Lumbosacral (L5-S1) load predictions of a...