In this paper,we discuss consensus problems for antagonistic networks with double integrator *** cases are analyzed:(1) undirected graphs with fixed topology on antagonistic networks;(2) undirected graphs with fixed t...
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ISBN:
(纸本)9781509009107
In this paper,we discuss consensus problems for antagonistic networks with double integrator *** cases are analyzed:(1) undirected graphs with fixed topology on antagonistic networks;(2) undirected graphs with fixed topology and time-delay on antagonistic *** both cases,distributed consensus protocols are proposed,with sufficient and necessary conditions *** is proved that the largest tolerable time-delay is only related to the largest eigenvalue of the graph ***,simulations are provided to demonstrate the obtained theoretical results.
Implicit camera transfer (ICT), which models the multi-valued mappings between two specific and stationary cameras, is a descent solution for the person re-identification problem of the surveillance system. It has the...
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ISBN:
(纸本)9781467369985
Implicit camera transfer (ICT), which models the multi-valued mappings between two specific and stationary cameras, is a descent solution for the person re-identification problem of the surveillance system. It has the properties of simplicity, computational efficiency and well utilizing negative training data. But it neglects the complementary relation between the descriptors of various views. And different appearance people have various most discriminative views among all the views, which are under diverse mappings. To tackle with this constraint, we model the multi-values mapping from different view independently, and fuse these transferring results of each view by LPBoost. Experimental results demonstrate that our scheme not only inherits most of the advantages (some sacrifice in speed, but still can run in real time for the same testing case in the ICT paper) of ICT but also obtains more discriminative mappings than ICT. In addition, our solution gains competitive performance on 2 challenging datasets.
Saliency propagation has been widely adopted for identifying the most attractive object in an image. The propagation sequence generated by existing saliency detection methods is governed by the spatial relationships o...
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ISBN:
(纸本)9781467369657
Saliency propagation has been widely adopted for identifying the most attractive object in an image. The propagation sequence generated by existing saliency detection methods is governed by the spatial relationships of image regions, i.e., the saliency value is transmitted between two adjacent regions. However, for the inhomogeneous difficult adjacent regions, such a sequence may incur wrong propagations. In this paper, we attempt to manipulate the propagation sequence for optimizing the propagation quality. Intuitively, we postpone the propagations to difficult regions and meanwhile advance the propagations to less ambiguous simple regions. Inspired by the theoretical results in educational psychology, a novel propagation algorithm employing the teaching-to-learn and learning-to-teach strategies is proposed to explicitly improve the propagation quality. In the teaching-to-learn step, a teacher is designed to arrange the regions from simple to difficult and then assign the simplest regions to the learner. In the learning-to-teach step, the learner delivers its learning confidence to the teacher to assist the teacher to choose the subsequent simple regions. Due to the interactions between the teacher and learner, the uncertainty of original difficult regions is gradually reduced, yielding manifest salient objects with optimized background suppression. Extensive experimental results on benchmark saliency datasets demonstrate the superiority of the proposed algorithm over twelve representative saliency detectors.
Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely...
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ISBN:
(纸本)9781467369985
Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter.
The most common concerns for users in cloud storage are data integrity, confidentiality and availability, so various data integrity auditing schemes for cloud storage have been proposed in the past few years, some of ...
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Pedestrian counting is an important component of video process.ng. Existing works with overhead cameras are mainly based on visual tracking, the robustness of which is rather limited. By proposing the novel spatial-te...
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ISBN:
(纸本)9781479957521
Pedestrian counting is an important component of video process.ng. Existing works with overhead cameras are mainly based on visual tracking, the robustness of which is rather limited. By proposing the novel spatial-temporal matrix, this paper aims to count pedestrians without tracking. As a result, a more robust and efficient pedestrian counting algorithm can be developed. Extensive experiment reveal that our system achieves satisfying performances in terms of both accuracy and efficiency.
The extraction of Canna edulis Ker. starch from its rhizome was performed using 2 different types of press （hydraulic press and screw press） and with the addition of Na-metabisulphite and NaOH （in the range of conc...
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The extraction of Canna edulis Ker. starch from its rhizome was performed using 2 different types of press （hydraulic press and screw press） and with the addition of Na-metabisulphite and NaOH （in the range of concentration 100 5000 ppm each）. The optimum condition for this process.was determined by Central Composite Design of experiment and the statistical calculation was solved by Design-Expert 7.0.0. The targets of the observed responses were high starch yield, low ash, low fiber, and high carbohydrate content. The results showed that the starch yield and the reduction of fiber were only influenced by the physical treatment whereas ash content in the product was influenced by both the NaOH concentration and physical treatment. The carbohydrate content in the extraction product was affected by NaOH, by the interaction between the concentrations of NaOH and Na 2 S 2 O 5 and also by the physical treatment. The hydraulic press gives much better responses compared to the screw press. But in the selected range of additives concentrations, the screw press gives a higher starch yield （30%-52%）.
Existing research work in the multimedia domain mainly focuses on image/video indexing, retrieval, annotation, tagging, re-ranking, etc. However, little work has been contributed to people's visual cognition. In t...
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A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaningful shots is the first pass ...
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A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaningful shots is the first pass for the task of video analysis, content-based video understanding. In this paper, a novel scheme based on improved two-dimensional entropy is proposed to complete the partition of video shots. Firstly, shot transition candidates are detected using a two-pass algorithm： a coarse searching pass and a fine searching pass. Secondly, with the character of two-dimensional entropy of the image, correctly detected transition candidates are further classified into different transition types whereas those falsely detected shot breaks are distinguished and removed. Finally, the boundary of gradual transition can be precisely located by merging the characters of two-dimensional entropy of the image into the gradual transition. A large number of video sequences are used to test our system performance and promising results are obtained.
Close-up (CU) is a photographic technique which tightly frames a person or an object. In movies, it is applied to guide audience attention and to evoke audience emotion. In this paper, we detect face CU, object CU, an...
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Close-up (CU) is a photographic technique which tightly frames a person or an object. In movies, it is applied to guide audience attention and to evoke audience emotion. In this paper, we detect face CU, object CU, and lean of movies, which are widely used to romance emotions. A lean consists of shots in a sequence, with a close-up shot as focus. A set of features are extracted by considering movie making techniques and human attention for CU detection. The features are average saliency, color entropy, color variance, face height, skin area, and texture scales. These features are tested through statistical hypothesis test to be significantly discriminating for CUs. Then, Support Vector Machine (SVM) is applied on these features to detect face CU and object CU. Based on the face CU and object CU detection result, lean is further detected by investigating the changing of the face/object size. Lean detection is of challenge due to the technique of montage. We solve this problem through color similarity estimation and SIFT point matching. Experimental results on four full length movies verify the effectiveness of the proposed method.
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