![]() ![]() Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. This review article surveys extensively the current progresses made toward video-based human activity recognition. The overall performance has been validated in the experiments. The particle filter at top level, which maintains the relation between target and feature points, estimates the tracked target state. The bottom level utilizes the Kanade-Lucas-Tomasi (KLT) feature point tracker which identifies the local point correspondence across image frames. A two layer tracking architecture is then utilized for tracking the detected target. A hybrid detection algorithm which combines the target's color and optical flow information is proposed here. Since the detection and tracking for different targets are performed at the same time on a moving camera platform, the detection and tracking processes must be fast and effective. ![]() In order to describe the relationship between the targets and camera in this tracking system, the input/output hidden Markov model (HMM) is applied here in the well-defined spherical camera coordinate. This paper presents a real-time tracking system to detect and track multiple moving objects on a controlled pan-tilt camera platform. ![]()
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