Abstract
This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.
Highlights
Various sensor platforms are used for persistently monitoring very large areas.For instance, Wide Area Motion Imagery (WAMI) systems on aerial platforms flying at 7000 feet and covering an area of a 2 mile radius can be used as an aid in disaster relief, emergency response, and traffic management [1]
Units in a complementary technology with in a complementary manner within the framework within the framework of real-time high performance computation architecture and (2) applies to of highof performance computation and (2)targets appliesbased to the application of detecting thereal-time application detecting and tracking architecture multiple moving on Wide Area
; the MapReduce program arranges the distributed clusters and runs the Graphic Processing Units (GPUs) tasks in a Compute Unified Device Architecture (CUDA) parallel computing platform. In this GPU and Cloud Moving Target Tracking (GC-MTT) MUltiple MOving Targets (MUMOTs) detection and tracking system, registration, background generation and foreground generation are performed in GPUs
Summary
Various sensor platforms are used for persistently monitoring very large areas. Wide Area Motion Imagery (WAMI) systems on aerial platforms flying at 7000 feet and covering an area of a 2 mile radius can be used as an aid in disaster relief, emergency response, and traffic management [1]. Such systems typically produce an overwhelmingly large amount of information as provided in the Columbus Large Image Format (CLIF) dataset [2]. Units (GPUs) in a complementary manner within the framework within the framework of real-time high performance computation architecture and (2) applies to of highof performance computation and (2)targets appliesbased to the application of detecting thereal-time application detecting and tracking architecture multiple moving on Wide Area.
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