Surveillance systems usually connect to multiple cameras for real-time video feeds. Traditionally, finding certain objects from these video feeds is a time-consuming and labor-intensive task, requiring manual monitori...
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Surveillance systems usually connect to multiple cameras for real-time video feeds. Traditionally, finding certain objects from these video feeds is a time-consuming and labor-intensive task, requiring manual monitoring or review by human operators. Such manual processes can lead to inefficiencies, especially when processing large amounts of footage in a short period. With the rapid development of AI-based computer vision, this research tries to enhance surveillance systems by integrating Pedestrian Attribute recognition (PAR) and Multi-Target Multi-Camera Tracking (MTMCT) technologies, creating a more efficient and automated solution. The PAR is to identify distinct appearance characteristics of a targeted person from images, enabling surveillance systems to identify and classify various attributes of pedestrians in a textual format, such as gender, age, hairstyle, types of clothing, accessories, etc. These attributes may also include more detailed features, such as posture and movement patterns, allowing for more precise search capabilities. On the other hand, the MTMCT is for identifying and tracking moving objects across multiple cameras, which requires a series of AI-based processes, including object detection and tracking on images from individual cameras, re-identify objects when moving from one camera to another, etc. This tracking process involves various complexities, including ensuring accurate re-identification of objects when they leave one camera’s view and enter another, which is key to maintaining continuous tracking. By integrating PAR and MTMCT technologies, a surveillance system can quickly locate target individuals from a large amount of image data based on space, time, and appearance information, which is extremely useful for various applications, including crime investigations, searching for missing persons, etc. In addition, as PAR models can extract local and global appearance features, these features can also help improve the re-identificati
The radiometric calibration accuracy of a hyperspectral imager is a key link in its quantitative application. The side-slither radiometric calibration can realize the high-frequency and full field of view relative rad...
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image super-resolution is the process of recovering high-resolution images from low-resolution inputs, which is crucial in low-level computer vision tasks. In recent years, progress in deep learning has significantly ...
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In this paper, the Recurrent Neural Network (RNN) model is introduced into the identification of radar emitters, which verifies the feasibility of RNN application to radar emitter identification, and the design proces...
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Detection of Building edges is crucial for building information extraction and description. Extracting structures from large-scale aerial images has been utilized for years in cartography. With commercially available ...
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Nowadays, object detection is an increasingly important technology in the field of remotesensingimageprocessing, which is applied to locate and identify high value ground objects in high resolution remotesensing i...
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Recognizing human action in videos at low resolution is of crucial importance for security monitoring and privacy protection. The previous methods usually carry out in a two-stage manner combined with super-resolution...
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Stereo estimation has made many advancements in recent years with the introduction of deep-learning. However the traditional supervised approach to deep-learning requires the creation of accurate and plentiful ground-...
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Edge detection can benefit many different industries and domains, including computer vision, machine learning, image analysis, remotesensing, thermal imaging, patternrecognition, and medical imaging. The technique o...
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Transmission line construction progress monitoring is critical for grid security control. This study proposed a method of using satellite remotesensing and UAV technology for transmission line construction progress d...
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