Contextual-based top-down saliency feature weighting for target detection

Rahman, Ibrahim M. H.; Hollitt, Christopher; Zhang, Mengjie

doi:10.1007/s00138-016-0754-x

Cited by 12 publications

(4 citation statements)

References 45 publications

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“…Of course, the enhancement technology can only highlight the characteristic information of the image, but cannot increase the valuable information contained in the image data itself. Only some scenes with blurred edges, texture characteristics, or poor contrast in the image can be enhanced [19].…”

Section: Image Processingmentioning

confidence: 99%

Intelligent Target Detection and Tracking Algorithm for Martial Arts Applications

Tang

2022

Wireless Communications and Mobile Computing

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Moving object detection and tracking is the basis and key technology for intelligent video surveillance, human-computer interaction, mobile robot and vehicle visual navigation, industrial robot system, and other applications. It has important applications in intelligent monitoring, human-computer interaction, visual navigation, and so on. Intelligent technology can greatly facilitate the monitoring of countless targets. This paper adopts the random motion model to describe the motion state of the target. Based on wireless communication and information security, this paper studies the communication and information security of the intelligent system of martial arts target detection and tracking algorithm, and the basic idea of mean-shift tracking algorithm is to use gradient climbing of probability density to find local optimal. This paper uses the background subtraction method based on the vibe algorithm to obtain the binary image of the foreground object; the shadow detection algorithm is used to remove the shadow of the foreground image; the haar-like (Haar) feature is selected as the feature of motion detection, and the feature value of the rectangular area is quickly calculated to describe the adjacent image area. The difference between the features, the final result image, and then the intelligent system for analysis. Experimental data shows that the time consumed by the tracking algorithm is less than 20 ms, which can meet the real-time requirements of ordinary target tracking systems. The average processing time of the hybrid modeling method is 62.8 ms, and the detection rate is 15.92 frames/SEC. The results show that the algorithm improves the utilization of particles, greatly reduces the complexity, and reduces the degradation of the particle filter.

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Section: Image Processingmentioning

confidence: 99%

Intelligent Target Detection and Tracking Algorithm for Martial Arts Applications

Tang

2022

Wireless Communications and Mobile Computing

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“…Top-down (TD) mechanism is slow task-driven mechanism that focus attention on target associated with task. This mechanism is the dominator factor in controlling gaze and shifting it towards the target during a high-level task [29]. In the process of taking photograph, the objects that attract human attention are usually placed in focus position, and the redundant information is blurred due to being placed out of focus.…”

Section: B Top-down Feature Mapmentioning

confidence: 99%

Robust Image Watermarking Based on Two-Layer Visual Saliency-Induced JND Profile

Wan

Wang

et al. 2019

IEEE Access

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Visual saliency (VS) is an important mechanism for defining which areas of an image will attract more attention of the HVS. Thus, VS can be employed to weight the just noticeable difference (JND) with different attention levels. Some VS-based JND profiles have been proposed in the DCT domain, which used the bottom-up features, such as luminance and texture only. Recently, the research about saliency detection has shown that a better saliency model considering both bottom-up features and top-down features will lead to a significant improvement for the overall saliency detection performance. In this paper, we propose a novel two-layer VS-induced JND profile, which is composed of the bottom-up features and the top-down feature extracted from DCT blocks in the transformed domain. In this model, the luminance and texture features are adapted to calculate the bottom-up features maps, while the top-down feature of focus is used to guide the generation of final salient regions since the camerapersons are used to facilitate the attention regions in focus. The proposed two-layer saliency-induced JND model is further applied to modulate the quantization step in the watermarking framework, which can make full use of its individual merits to achieve a better tradeoff between fidelity and robustness. The experimental results show that the proposed scheme has superior performance than the previous watermarking schemes.

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“…Among them, the desktop virtualization technology can make that the users do not have to stick to the existing hardware entity. Instead, they can access to the system on the remote server at any time and place through any devices (such as a client phone, pad, and mobile phone) [5].…”

Section: Cloud Computing and Virtual Technologymentioning

confidence: 99%

Design of Wireless Sensing Virtual Cloud Desktop System Based on ARM-Linux

Han

2017

Int. J. Onl. Eng.

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Aiming at exploring the wireless sensing network with mass processing in data collection, an embedded wireless sensor system based on ARM-Linux is put forward and designed. The whole system is mainly divided into wireless ZigBee sensing node group part, ARM data processing part, and virtual cloud desktop terminal part. Users’ terminal can be connected to the cloud system server through wired or wireless ways. And it is possible to view user system data and wireless terminal data by logging in to an individual account. The results showed that the system can be applied in a lot of fields, such as intelligent transportation, health care, smart home and so on. Based on the above findings, it is concluded that it is important for information aggregation and remote fast monitoring.

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Contextual-based top-down saliency feature weighting for target detection

Cited by 12 publications

References 45 publications

Intelligent Target Detection and Tracking Algorithm for Martial Arts Applications

Intelligent Target Detection and Tracking Algorithm for Martial Arts Applications

Robust Image Watermarking Based on Two-Layer Visual Saliency-Induced JND Profile

Design of Wireless Sensing Virtual Cloud Desktop System Based on ARM-Linux

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