Moving object detection which has attracted wide attention is the critical issue of computer vision. Consequently, the low-rank and sparse decomposition (LRSD) has been a powerful technology for extracting the moving ...
Moving object detection which has attracted wide attention is the critical issue of computer vision. Consequently, the low-rank and sparse decomposition (LRSD) has been a powerful technology for extracting the moving object from videos which has achieved improvement for moving object detection. However, it still has some defaults such as the lower degree for approximating the low-rank and sparsity components, ignoring the spatial information of videos, being sensitive to noise, and so on. To address these problems mentioned above, we propose a new LRSD method which is named nonconvex norm and Laplacian scale mixture with salient map (NNLSMSM). It adopts the nonconvex $$\gamma $$ -norm and the Laplacian scale mixture (LSM) to approximate the low-rank and sparsity components of traditional LRSD model for enhancing the degree of approximating. Meanwhile, a salient map mechanism which can effectively capture the spatial information from videos is introduced to NNLSMSM. In addition, we extend our proposed NNLSMSM method to a robust NNLSMSM (RNNLSMSM) method for enhancing its robustness via introducing a noise item. It can effectively solve the problem of being sensitive to noise. In addition, we adopt the alternating direction method of multipliers (ADMM) to solve our proposed NNLSMSM and RNNLSMSM methods. At last, extensive experiments which are performed on various popular datasets by some state-of-the-art methods demonstrate the effectiveness and superiority of our proposed NNLSMSM and RNNLSMSM methods.
The traditional Poisson model in the modern data networks have been ineffective and cannot reflect the real flow trend. However, since Hosking discovers the network traffic self-similarity, self-similar models have co...
详细信息
The traditional Poisson model in the modern data networks have been ineffective and cannot reflect the real flow trend. However, since Hosking discovers the network traffic self-similarity, self-similar models have continued to emerge, this article improved FARIMA model based on time compensation. We put forward a sliding FARIMA model which fixes the time delay of FARIMA model and analyzed the model's application in the anomaly detection of network.
This paper focused on the study of cognitive networks (CNs) oriented multi-parameter constraint Quality of Service (QoS) routing optimization. With the foundation of CNs multi-parameter QoS routing requirement, referr...
详细信息
Haptic technology enables robots to touch and understand the interactions between objects in the reality. Advanced haptic sensing systems can not only collect pressure, temperature and stiffness of touched objects, bu...
Haptic technology enables robots to touch and understand the interactions between objects in the reality. Advanced haptic sensing systems can not only collect pressure, temperature and stiffness of touched objects, but also avoid destructive operations, and assist in navigation and posture control for robots. In order to smoothly interact with different types of objects, in the haptic system, it is necessary to develop haptic object recognition methods for effective haptic perception capability. However, compared to RGB images, haptic images collected by opticallybased haptic sensors are similar in appearance, which makes traditional convolutional neural networks (e.g.,ResNet, VGG, etc.) ineffective. Therefore, in this paper, we are inspired by popular attention mechanism and multi-scale strategies, and propose a cross-scale attention based haptic object recognition network for object-robot interaction. In particular, On the one hand, we design a cross-scale attention module in convolutional neural networks to acquire spatial contextual feature. On the other hand, we design a learnable bilinear fusion strategy to integrate above spatial contextual feature with original haptic feature, so as to effectively discriminate haptic images. Experimental results on ViTac dataset have shown the effectiveness of our approach.
With the exploration of the virtual world, 3D reconstruction has drawn increasing attention. To achieve large-scale and low-latency virtual world interaction, data volume compression and visual experience are indispen...
详细信息
ISBN:
(数字)9798350378412
ISBN:
(纸本)9798350378429
With the exploration of the virtual world, 3D reconstruction has drawn increasing attention. To achieve large-scale and low-latency virtual world interaction, data volume compression and visual experience are indispensable, but they tend to conflict in practice. Based on the above issues, we propose a semantic communication-based image transmission and 3D generation scheme (SV-3D BSC). First, we perform semantic segmentation on the image at the transmitter. In addition, at the receiver, we analyze the semantic symbols based on a common knowledge base and preliminarily restore the image through a generative adversarial network (GAN). Next, the restored image is further optimized for generating a Neural Radiance Fields (NeRF) representation. This scheme can greatly compress the data volume of virtual interaction and generate exquisite 3D models. Finally, experiments have shown that our scheme saves a lot of bandwidth and generates reasonable and colorful 3D models.
AODV protocol is a comparatively mature on-demand routing protocol in mobile ad hoc networks. However, the traditional AODV protocol seems less than satisfactory in terms of delivery reliability. This paper presents a...
详细信息
AODV protocol is a comparatively mature on-demand routing protocol in mobile ad hoc networks. However, the traditional AODV protocol seems less than satisfactory in terms of delivery reliability. This paper presents an AODV with reliable delivery (AODV-RD), a link failure fore-warning mechanism, metric of alternate node in order to better select, and also repairing action after primary route breaks basis of AODV-BR. Performance comparison of AODV-RD with AODV-BR and traditional AODV using ns-2 simulations shows that AODV-RD significantly increases packet delivery ratio (PDR). AODV-RD has a much shorter end-to-end delay than AODV-BR. It both optimizes the network performance and guarantees the communication quality.
In this paper, we propose a robust object tracking algorithm based on SURF. First, we adopt a two-stage matching method to improve the accuracy of SURF matching points. Then a template update method is used to deal wi...
详细信息
In this paper, we propose a robust object tracking algorithm based on SURF. First, we adopt a two-stage matching method to improve the accuracy of SURF matching points. Then a template update method is used to deal with the problem of object appearance change. Next we use matching points between new template and candidate region to locate the initial position of object. As template update and object occlusion will cause the accumulation of tracking errors, therefore, at last fixed template is used to correct object's position. For those frames which have little matching points, we use Meanshift instead of SURF to track object. The experiments demonstrate that our work is robust and can track object accurately in complex environments.
With the previous method based on the signal strength of the three-beam interference source [1], after studying and deriving the antenna gain pointing model, this paper proposes a single-star interference source local...
详细信息
作者:
Junqing ZhangRuchuan WangYisheng QianQianyi WangCollege of Computer
Nanjing University of Posts and Telecommunications Nanjing Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education
The main study of traditional probability coverage problem in wirelesssensornetworks(WSNs) is aiming at twodimensional space, however, most practical applications of wirelesssensornetwork is placed in a three-dime...
详细信息
The main study of traditional probability coverage problem in wirelesssensornetworks(WSNs) is aiming at twodimensional space, however, most practical applications of wirelesssensornetwork is placed in a three-dimensional sensornetworks. Therefore, probability model is introduced for three-dimensional WSNs. This paper presents a method that using Voronoi divide to control the Scheduling of the probability model nodes in the target area. Also, a coverage control algorithm based on probability model(PMCCA) is proposed. We verify the effectiveness and the practice of PMCCA algorithm by comparing PMCCA algorithm to another algorithm in simulation experiment.
This paper studies the system performance of a multiuser dual-hop satellite relaying network where the threshold-based decode-and-forward (DF) is adopted at the relay. Specifically, we can first get the maximum signal...
详细信息
暂无评论