Clinical Patient Tracking in the Presence of Transient and Permanent Occlusions via Geodesic Feature
This addresses a domain-specific challenge in clinical rehabilitation by improving patient tracking accuracy under occlusions, though it is incremental as it builds on existing tracking methods.
The paper tackles the problem of tracking spinal cord injury patients during rehabilitation despite occlusions from clinicians and equipment, by introducing a geodesic distance-based feature and multi-hypothesis tracking, achieving robustness to deformations and occlusions in simulations.
This paper develops a method to use RGB-D cameras to track the motions of a human spinal cord injury patient undergoing spinal stimulation and physical rehabilitation. Because clinicians must remain close to the patient during training sessions, the patient is usually under permanent and transient occlusions due to the training equipment and the movements of the attending clinicians. These occlusions can significantly degrade the accuracy of existing human tracking methods. To improve the data association problem in these circumstances, we present a new global feature based on the geodesic distances of surface mesh points to a set of anchor points. Transient occlusions are handled via a multi-hypothesis tracking framework. To evaluate the method, we simulated different occlusion sizes on a data set captured from a human in varying movement patterns, and compared the proposed feature with other tracking methods. The results show that the proposed method achieves robustness to both surface deformations and transient occlusions.