In surveillance video, target tracking is an important part. Based on imageprocessing technology, this paper studies a real-time and effective method to collect and recognize camera motion information. Firstly, the i...
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ISBN:
(纸本)9798350310801
In surveillance video, target tracking is an important part. Based on imageprocessing technology, this paper studies a real-time and effective method to collect and recognize camera motion information. Firstly, the influence of visual dead angle and illumination on recognition is analyzed. Secondly, according to the characteristic of background light intensity, the corresponding algorithm is designed to realize the positioning and tracking control strategy of the target and surrounding environment scenery. Finally, the correctness of the method is verified by MATLAB simulation software, so as to obtain a better and scalable scheme, which is more economical and feasible after the occlusion rate is minimized.
The execution of complex functions and high computational tasks remains a major obstacle to efficient and transparent real-timeprocessing. Overcoming these challenges is essential to unlocking the full potential of i...
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The imperceptible color vibration method, which embeds imperceptible patterns in display images through rapid chromatic changes, enables the presentation of information to machines while maintaining the viewing experi...
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ISBN:
(纸本)9798331529543;9798331529550
The imperceptible color vibration method, which embeds imperceptible patterns in display images through rapid chromatic changes, enables the presentation of information to machines while maintaining the viewing experience of users. However, when markers are embedded in videoimages, decoding becomes challenging during periods with significant interframe differences, which adds noise to the decoding. In this study, we enhanced the signal-point distance by embedding two quadrature chromatic changes within the color space across the entire image. Additionally, we employed soft-decision decoding, which involves accumulating multiple confidence values per pixel, thereby enabling robust decoding during periods with significant interframe differences in videoimages. Our evaluation confirmed that the proposed method significantly improves the decoding rate compared to conventional techniques. Furthermore, we measured the time required for decoding and verified the effectiveness of the proposed soft-decision decoding method.
With the rapid development of autonomous driving applications, there is an increasing demand for high-speed vision sensors like spike cameras. However, the data transmission and storage requirements are becoming incre...
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With the rapid development of autonomous driving applications, there is an increasing demand for high-speed vision sensors like spike cameras. However, the data transmission and storage requirements are becoming increasingly burdensome due to the high temporal resolution, such as 40,000 Hz. To resolve this problem, we propose a pixel-level attention-based data compression method for the spike camera. First the input spike data are partitioned into two block types by pixel-level attention-based method. Then, the two blocks are condensed using different methods and side information marking is transmitted for spike decoding. Finally, the condensed spike and side information marking are compressed into a binary stream for storage. The experimental results show that our method achieves higher compression efficiency than conventional methods. The decompressed spike can also reconstruct the image with better visual quality.
image enhancement is frequently used to improve the input image's visual quality. Experts also utilize image enhancement as a preprocessing method rather than a complete solution in computer vision applications. I...
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image enhancement is frequently used to improve the input image's visual quality. Experts also utilize image enhancement as a preprocessing method rather than a complete solution in computer vision applications. In addition, consumers want to acquire digital images with good real-life contrast, which balances the number of pixels with darker and brighter intensity values. Unfortunately, acquired images become too dark or bright to inspect visually due to bad lighting or unwanted reflections. These undesired images may cause problems in applications such as medical imaging, satellite imagery, or UAV imaging. Therefore, this study introduces an image enhancement method using local and global enhancements to overcome the above-mentioned issues. Besides image quality, there is another problem with imageprocessing applications, such as image size. As the image size gets larger, computers usually take much more time to complete the given task. Parallel computing is a method that takes advantage of several processing units on the same system using some libraries or APIs. Since it is easy to use and requires fewer sequential code changes, we preferred to use OpenMP in this study to parallelize sequential implementation. Although the proposed work is developed in C++ and is based on a small sample of dark images, the findings suggest that proposed parallel implementations can be very efficient and feasible in other programming languages for different types of imageprocessing operations. Then, we compared the performance of both sequential and parallel implementations. Based on the experimental results, we observed that the proposed parallel implementation of the reference algorithm runs up to 38 times faster than the sequential version on a cloud computing platform with 48 physical cores.
In order to monitor the video state changes of safe human settlements in realtime, a Mean Shift algorithm is proposed. The video monitoring images collected in realtime were preprocessed with enhancement and denoisi...
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Traditional video analytics are typically performed on a single node having limited processing power and vertical scalability, resulting in a lack of real-time performance and potential single point failures. To addre...
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Foggy weather conditions frequently reduce visibility and degrade video stream quality, affecting a variety of real-world applications such as surveillance, autonomous navigation, and outdoor video recording. This pap...
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Drowning is a significant public health concern. A video drowning detection algorithm is a helpful tool for finding drowning victims. However, there are three challenges that drowning detection research typically enco...
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Drowning is a significant public health concern. A video drowning detection algorithm is a helpful tool for finding drowning victims. However, there are three challenges that drowning detection research typically encounters: a lack of actual drowning video data, subtle early drowning traits, and a lack of realtime. In this paper, the authors propose an underwater computer vision based drowning detection device composed of embedded AI devices, camera, and waterproof case to solve the above problems. The detection device utilizes the high-performance computing of Jetson Nano to realize real-time detection of drowning events through the proposed drowning detection algorithm on the acquired underwater video stream. The proposed drowning detection algorithm primarily consists of two stages: in the first step, to successfully solve the interference of the surroundings and to give a trustworthy basis for video drowning detection, the YOLOv5n network is used to detect the near-vertical human body based on the characteristics of the drowning person. In the second stage, the authors propose a lightweight drowning detection network (DDN) based on a deep Gaussian model for fast feature vector detection. The lightweight DDN is combined with the Gaussian model to detect anomaly in the high-level semantic features, which has higher robustness and solves the lack of drowning videos. The experimental results show that the proposed drowning detection algorithm has good comprehensive performance and practical application value.
Human image animation aims to generate a human motion video from the inputs of a reference human image and a target motion video. Current diffusion-based image animation systems exhibit high precision in transferring ...
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