Many computer applications require the manipulation of large data arrays. These applications can behave badly under a paged virtual memory (VM) system, due to poor memory access patterns. One solution to this problem ...
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nedestrian detection is highly valued in intelligent surveillance systems. Most existing pedestrian datasets are autonomously collected from non-surveillance videos, which result in significant data differences betwee...
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ISBN:
(纸本)9783319545264;9783319545257
nedestrian detection is highly valued in intelligent surveillance systems. Most existing pedestrian datasets are autonomously collected from non-surveillance videos, which result in significant data differences between the self-collected data and practical surveillance data. The data differences include: resolution, illumination, view point, and occlusion. Due to the data differences, most existing pedestrian detection algorithms based on traditional datasets can hardly be adopted to surveillance applications directly. To fill the gap, one surveillance pedestrian image dtaset (SPID), in which all the images were collected from the on-using surveillance systems, was constructed and used to evaluate the existing pedestrian detection (PD) methods. The dataset covers various surveillance scenes and pedestrian scales, view points, and illuminations. Four traditional PD algorithms using hand-crafted features and one deep-learning-model based deep PD methods are adopted to evaluate their performance on the SPID and some well-known existing pedestrian datasets, such as INRIA and Caltech. The experimental ROC curves show that: The performance of all these algorithms tested on SPID is worse than that on INRIA dataset and Caltech dataset, which also proves that the data differences between non-surveillance data and real surveillance data will induce the decreasing of PD performance. The main factors include scale, view point, illumination and occlusion. Thus the specific surveillance pedestrian dataset is very necessary. We believe that the release of SPID can stimulate innovative research on the challenging and important surveillance pedestrian detection problem. SPID is available online at: http://***/best/Data/List/Datasets.
Contrast and brightness of digital images can be adjusted by contrast enhancement. Mostly digital images are stored in Jpeg format in real application like Internet and Mobile phones. In order to reduce the size digit...
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ISBN:
(纸本)9781479972258
Contrast and brightness of digital images can be adjusted by contrast enhancement. Mostly digital images are stored in Jpeg format in real application like Internet and Mobile phones. In order to reduce the size digital images are compressed with high, middle and low quality factor. Move and paste type of images are created by malicious person, in which contrast of one source image is enhanced to match the other source image. Detecting global contrast enhancement on previously Jpeg compressed images can identified using global contrast enhancement detection algorithm. Zero height gab bins of histogram used to identify the global contrast enhancement. Zero height gap bins/peaks are used to identify the composite images created by contrast enhancement. Contrast enhancement technique aimed at detecting image tampering has grown in different applications area such as law enforcement, surveillance. Composite detection algorithm and global contrast enhancement detection algorithms are presented here. In order to increase the imageprocessing task parallel approach is used.
Computational modeling of visual attention has been a research field focused on emulating the behavior of biological visual systems in a given scenario, by using mechanisms developed for fixation prediction or salient...
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ISBN:
(纸本)9781510640412
Computational modeling of visual attention has been a research field focused on emulating the behavior of biological visual systems in a given scenario, by using mechanisms developed for fixation prediction or salient region detection. In the literature, different approaches have been presented to emulate the interactions that occur in the early vision system of biological structures. However, mathematical modeling of these systems applying theories related to fractional operators could outperform the existing models. In this paper, we present a fractional bio-inspired filter for salient color detection in natural scenarios, based on the behavior and distribution of the cone photoreceptors cells in the retina. The filter was compared with two classic saliency algorithms over a natural color image dataset in terms of saliency prediction and processing time, using a Similarity (SIM) score and runtime performance, respectively. Our approach reach the second best result in therms of saliency prediction with a 48,9% of SIM with ground truth fixations maps and the fastest time response, with an average time of 0.12 s when processing a high resolution image, being 25% faster than Itti et al. algorithm, one of the most applied in robotic vision tasks.
Blueprints are documents that contain the drawing of a design and the information that explains this design. Recently, the task to automatically recognize the information in the blueprint documents has become required...
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ISBN:
(纸本)9783031214370;9783031214387
Blueprints are documents that contain the drawing of a design and the information that explains this design. Recently, the task to automatically recognize the information in the blueprint documents has become required. Segmenting the frame and tables in the blueprint is the first step of understanding the blueprint document. In this paper, we explain an automated method for frame and table segmentation. The proposed method processes the blueprint as an image and defines all the parts (pixels) of the blueprint that belongs to the frame or tables. It finds all the lines in the blueprint's image and decide which combinations of lines construct frame and tables. It can process blueprints that have high resolution. The proposed method allows to isolate frame and tables in the blueprint document. We achieved an accuracy of 99% for excellent quality documents.
The drive behind this research is to devise an autonomous method for dynamically detecting a movable coloured object within ambiguous environments. Based on a study of different methods of automation using image proce...
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In this paper we show a reconfigurable hardware architecture for the acceleration of video-based driver assistance applications in future automotive systems. The concept is based on a separation of pixel-level operati...
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ISBN:
(纸本)9783981080124
In this paper we show a reconfigurable hardware architecture for the acceleration of video-based driver assistance applications in future automotive systems. The concept is based on a separation of pixel-level operations and high level application code. Pixel-level operations are acceler ated by coprocessors, whereas high level application code is implemented fully programmable on standard PowerPC CPU cores to allow flexibility for new algorithms. In addition, the application code is able to dynamically reconfigure the coprocessors available on the system, allowing for a much larger set of hardware accelerated functionality than would normally fit onto a device. This process makes use of the partial dynamic reconfigurarion capabilities of Xilinx Virtex FPGAs.
In this paper, we propose a novel low-power listening scheme that is comprised of non-deterministic preamble sampling periods and demonstrate how the mean of these sampling periods can be varied through the use of a p...
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The contrast enhancement of infrared image is useful and important to the infrared image system. The current techniques of local enhancing exists either over-enhancing or high complexity problems. In this paper, we pr...
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ISBN:
(纸本)9780819488411
The contrast enhancement of infrared image is useful and important to the infrared image system. The current techniques of local enhancing exists either over-enhancing or high complexity problems. In this paper, we propose a novel contrast enhancement algorithm which combines histogram equalization based methods (HEBM) and an improved unsharp masking based methods (UMBM). This proposed algorithm uses HEBM to achieve global contrast enhancement and UMBM to achieve local contrast enhancement. Some elaborate strategies are applied to the algorithm to avoid the over-enhancement and magnification of noise when contrast is enhanced. The article is organized as follows. First, we review the techniques developed in the literature for contrast enhancement. After then, we introduce the new algorithm in details. The performance of the proposed method is studied on experimental IR data and compared with those yielded by two well established algorithms. The developed algorithm has good performance in global contrast and local contrast enhancement with noise and artifact suppression.
algorithms for imageprocessing and computer vision are natural candidates for high performance computing systems. This paper presents a reconfigurable parallel architecture prototype for imageprocessing base on larg...
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ISBN:
(纸本)1424403316
algorithms for imageprocessing and computer vision are natural candidates for high performance computing systems. This paper presents a reconfigurable parallel architecture prototype for imageprocessing base on large scale FPGA computing. The introduced architecture can cover a wide range of real-time computer vision applications from pre-processing operations to low-level interpretation. In order to reduce the memory accessing time and communication latency, prime memory system for neighborhood operations or other data structures and FPGA-based transfer interconnection networks were designed in the introduced prototype system. This proposed architecture allows the user to program the system in both high-lever (soft-programming) and low-level (hard-programming).
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