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One of the very first steps astronomers working in stellar physics perform to advance in their studies, is to determine the most common/relevant physical parameters of the objects of study (effective temperature, bolometric luminosity,…
Human pose estimation, particularly in athletes, can help improve their performance. However, this estimation is difficult using existing methods, such as human annotation, if the subjects wear loose-fitting clothes such as ski/snowboard…
This paper proposes an image-processing-based method for personalization of calorie consumption assessment during exercising. An experiment is carried out where several actions are required in an exercise called broadcast gymnastics,…
An innovative approach of gaining insight into motor skills involved in human body flight is proposed. The key idea is the creation of a model autonomous system capable of virtually performing skydiving maneuvers. A dynamic skydiver model…
Rigid body systems usually consider measurements of the pose of the body using onboard cameras/LiDAR systems, that of linear acceleration using an accelerometer and of angular velocity using an IMU. However, the measurements of the linear…
The filming of sporting events projects and flattens the movement of athletes in the world onto a 2D broadcast image. The pixel locations of joints in these images can be detected with high validity. Recovering the actual 3D movement of the…
This work presents, the classification of user activities such as Rest, Walk and Run, on the basis of frequency component present in the acceleration data in a wireless sensor network environment. As the frequencies of the above mentioned…
Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains. Detecting errors in workout form naturally requires estimating human's body pose. However, off-the-shelf pose estimators…
A number of computer vision tasks exploit a succinct representation of the visual content in the form of sets of local features. Given an input image, feature extraction algorithms identify a set of keypoints and assign to each of them a…
Injury prevention in sports requires understanding how bio-mechanical risks emerge from movement patterns captured in real-world scenarios. However, identifying and interpreting injury prone events from raw video remains difficult and…
As we move through the world, the pattern of light projected on our eyes is complex and dynamic, yet we are still able to distinguish between moving and stationary objects. We propose that humans accomplish this by exploiting constraints…
Gait analysis from videos obtained from a smartphone would open up many clinical opportunities for detecting and quantifying gait impairments. However, existing approaches for estimating gait parameters from videos can produce physically…
Judging a gymnastics routine is a noisy process, and the performance of judges varies widely. In collaboration with the F\'ed\'eration Internationale de Gymnastique (FIG) and Longines, we are designing and implementing an improved…
We consider a bivariate process $X_t=(X^1_t,X^2_t)$, which is observed on a finite time interval $[0,T]$ at discrete times $0,\Delta_n,2\Delta_n,....$ Assuming that its two components $X^1$ and $X^2$ have jumps on $[0,T]$, we derive tests…
The accuracy and efficiency of human body pose estimation depend on the quality of the data to be processed and of the particularities of these data. To demonstrate how dance videos can challenge pose estimation techniques, we proposed a…
Pedestrian attribute recognition in surveillance scenarios is still a challenging task due to the inaccurate localization of specific attributes. In this paper, we propose a novel view-attribute localization method based on attention…
Cue points indicate possible temporal boundaries in a transition between two pieces of music in DJ mixing and constitute a crucial element in autonomous DJ systems as well as for live mixing. In this work, we present a novel method for…
Motivated by recent work on studying massive imaging data in various neuroimaging studies, we propose a novel spatially varying coefficient model (SVCM) to spatially model the varying association between imaging measures in a…
As video generation models advance rapidly, assessing the quality of generated videos has become increasingly critical. Existing metrics, such as Fr\'echet Video Distance (FVD), Inception Score (IS), and ClipSim, measure quality primarily…
Video anomaly detection (VAD) identifies suspicious events in videos, which is critical for crime prevention and homeland security. In this paper, we propose a simple but highly effective VAD method that relies on attribute-based…