| 1. |
- Ge, Chenjie, 1991, et al.
(författare)
-
Co-saliency detection via inter and intra saliency propagation
- 2016
-
Ingår i: Signal Processing: Image Communication. - 0923-5965. ; 44, s. 69-83
-
Tidskriftsartikel (refereegranskat)abstract
- The goal of salient object detection from an image is to extract the regions which capture the attention of the human visual system more than other regions of the image. In this paper a novel method is presented for detecting salient objects from a set of images, known as co-saliency detection. We treat co-saliency detection as a two-stage saliency propagation problem. The first inter-saliency propagation stage utilizes the similarity between a pair of images to discover common properties of the images with the help of a single image saliency map. With the pairwise co-salient foreground cue maps obtained, the second intra-saliency propagation stage refines pairwise saliency detection using a graph-based method combining both foreground and background cues. A new fusion strategy is then used to obtain the co-saliency detection results. Finally an integrated multi-scale scheme is employed to obtain pixel-level co-saliency maps. The proposed method makes use of existing saliency detection models for co-saliency detection and is not overly sensitive to the initial saliency model selected. Extensive experiments on three benchmark databases show the superiority of the proposed co-saliency model against the state-of-the-art methods both subjectively and objectively.
|
|
| 2. |
- Liu, Fanghui, et al.
(författare)
-
Robust visual tracking via constrained correlation filter coding
- 2016
-
Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655. ; 84, s. 163-169
-
Tidskriftsartikel (refereegranskat)abstract
- Unconstrained correlation filters based trackers achieve superior performance with high speed in visual tracking. However, such unconstrained correlation filters do not impose any hard constraint to their responses to have a certain value, which brings about classification ambiguity on intractable samples (i.e., two similar samples from different classes). To tackle this issue, in this paper, constrained correlation filter is introduced into visual tracking framework to alleviate classification ambiguity for more accurate target location. By imposing distinguishable hard constraints on the response map to different classes, a supervised coding method is proposed to encode various candidate samples by a discriminative filter bank. The learned high-level feature vectors are sent to a Naive Bayes classifier to separate the target from the background. Besides, parameters updating schemes in the constrained filter and classifier are introduced to adapt to appearance changes of the target with less possibility of drifting. Both qualitative and quantitative evaluations on Object Tracking Benchmark (OTB) show that the proposed tracking method achieves favorable performance compared with other state-of-the-art methods.
|
|
| 3. |
- Liu, Fanghui, et al.
(författare)
-
Robust visual tracking via inverse nonnegative matrix factorization
- 2016
-
Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781479999880 ; 2016-May, s. 1491-1495
-
Konferensbidrag (refereegranskat)abstract
- The establishment of robust target appearance model over time is an overriding concern in visual tracking. In this paper, we propose an inverse nonnegative matrix factorization (NMF) method for robust appearance modeling. Rather than using a linear combination of nonnegative basis vectors for each target image patch in conventional NMF, the proposed method is a reverse thought to conventional NMF tracker. It utilizes both the foreground and background information, and imposes a local coordinate constraint, where the basis matrix is sparse matrix from the linear combination of candidates with corresponding nonnegative coefficient vectors. Inverse NMF is used as a feature encoder, where the resulting coefficient vectors are fed into a SVM classifier for separating the target from the background. The proposed method is tested on several videos and compared with seven state-of-the-art methods. Our results have provided further support to the effectiveness and robustness of the proposed method.
|
|
| 4. |
- Liu, Fanghui, et al.
(författare)
-
Visual Tracking via Nonnegative Regularization Multiple Locality Coding
- 2015
-
Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - 1550-5499. - 9780769557205 ; 2015-February, s. 912-920
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a novel object tracking method based on approximated Locality-constrained Linear Coding (LLC). Rather than using a non-negativity constraint on encoding coefficients to guarantee these elements nonnegative, in this paper, the non-negativity constraint is substituted for a conventional ℓ2 norm regularization term in approximated LLC to obtain the similar nonnegative effect. And we provide a detailed and adequate explanation in theoretical analysis to clarify the rationality of this replacement. Instead of specifying fixed K nearest neighbors to construct the local dictionary, a series of different dictionaries with pre-defined numbers of nearest neighbors are selected. Weights of these various dictionaries are also learned from approximated LLC in the similar framework. In order to alleviate tracking drifts, we propose a simple and efficient occlusion detection method. The occlusion detection criterion mainly depends on whether negative templates are selected to represent the severe occluded target. Both qualitative and quantitative evaluations on several challenging sequences show that the proposed tracking algorithm achieves favorable performance compared with other state-of-the-art methods.
|
|
| 5. |
- Wang, Di, et al.
(författare)
-
Transmission of clones of carbapenem-resistant Escherichia coli between a hospital and an urban wastewater treatment plant*
- 2023
-
Ingår i: Environmental Pollution. - : Elsevier. - 0269-7491 .- 1873-6424. ; 336
-
Tidskriftsartikel (refereegranskat)abstract
- Carbapenem-resistant Enterobacterales (CRE) constitute an urgent threat to worldwide public health. The spread of CRE is facilitated by transmission via the environment. Wastewater treatment plants (WWTPs) are considered to be important sources of antibiotic resistance and hot spots of antibiotic-resistant bacteria (ARB) which can facilitate dissemination of antibiotic resistance genes. In this study, water samples were collected over one year from a WWTP in Jinan, Shandong province, China, from different functional sites in the wastewater treatment process. Carbapenem-resistant Escherichia coli (CREC) were isolated by selective cultivation and whole-genome sequenced to investigate the occurrence and characteristics of CREC in the WWTP. A total of 77 CREC isolates were included in the study and the detection rate of CREC in the WWTP water inlet was found to be 85%. An additional 10 CREC were isolated from a nearby teaching hospital during the sampling period and included for comparison to the environmental isolates. Susceptibility testing showed that all CREC were multidrug-resistant. 6 different carbapenem resistance genes (CRGs) were detected, including blaNDM-5 (n = 75), blaNDM-1 (n = 6), blaNDM-4 (n = 3), blaNDM-6 (n = 1), blaNDM-9 (n = 1), and blaKPC-2 (n = 4). 42 CREC isolates were whole-genome sequenced with Illumina short-read sequencing. 11 of these were also sequenced with Nanopore long-read sequencing. Plasmids carrying CRGs were found to belong to IncX3 (n = 35), IncFII (n = 12), IncFIA (n = 5), IncFIB (n = 2), IncC (n = 1), and IncP6 (n = 1). Clonal dissemination of CREC belonging to ST167, ST448, and ST746 was observed between different parts of the WWTP. Furthermore, isolates from the WWTP, including an isolate belonging to the high-risk ST167 strain, were found to be clonally related to CREC isolated at the hospital. The spread of CRGs is of considerable concern and strategies to prevent environmental dissemination of this contaminant urgently needs to be implemented.
|
|
