Multiple objects tracking with a surveillance camera system

Increasing use of CCTV for city and building surveillance has given rise to an environment where an object (a person) might traverse through the field of vi>vv of many cameras. In this paper we explore the problem of tracking multiple objects in a multi camera environment, which is a highly addressed area in computer vision. Our research involves real time tracking of objects while they are moving in a multi camera environment with non-overlapping field of v/ewjr and detecting them when they re-uppear in the same or another camera in the same system. Previous methods of using offline trained classifiers with huge databases are time consuming and have the drawback of incapability of detecting arbitrarily selected objects. We address this issue by online training with the initial sample given and is based on the TLD (Tracking, Learning, Detection) framework. We extend the idea to formulate our methodology to create a framework that can track multiple objects in multiple video streams in real time. We have developed upper layers as a thread based architecture in order to incorporate multiple video feeds and to handle multiple objects. We have integrated CUDA (Computer Unified Device Architecture) programming model to add parallelism to independent processes and execute compute intensive algorithms. GPU computing offers an ideal computing environment to improve our framework. Our optimization of the algorithms, careful usage of parallel computing and proper utilization of GPU resources have contributed in achieving a processing time of less than 60ms for multi objects in multi camera environment

COVID-19 and Acute Heart Failure: Screening the Critically Ill - A Position Statement of the Cardiac Society of Australia and New Zealand (CSANZ).

Up to one-third of COVID-19 patients admitted to intensive care develop an acute cardiomyopathy, which may represent myocarditis or stress cardiomyopathy. Further, while mortality in older patients with COVID-19 appears related to multi-organ failure complicating acute respiratory distress syndrome (ARDS), the cause of death in younger patients may be related to acute heart failure. Cardiac involvement needs to be considered early on in critically ill COVID-19 patients, and even after the acute respiratory phase is passing. This Statement presents a screening algorithm to better identify COVID-19 patients at risk for severe heart failure and circulatory collapse, while balancing the need to protect health care workers and preserve personal protective equipment (PPE). The significance of serum troponin levels and the role of telemetry and targeted transthoracic echocardiography (TTE) in patient investigation and management are addressed, as are fundamental considerations in the management of acute heart failure in COVID-19 patients