中国科学院机构知识库网格系统: 检索

Research on data association and detection algorithm in point target tracking 会议论文 OAI收割
Beijing, China, 2023-07-25
作者: He, Xiaokun; Li, Peng; Liu, Wen

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收藏 | 浏览/下载：8/0 | 提交时间：2024/02/07

Point target Multi-feature fusion Data association Point target detection

Biological Eagle-eye Inspired Target Detection for Unmanned Aerial Vehicles Equipped with a Manipulator 期刊论文 OAI收割
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 741-752
作者: Yi-Min Deng; Si-Yuan Wang

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收藏 | 浏览/下载：6/0 | 提交时间：2024/04/23

Unmanned aerial vehicle (UAV), eagle eye, multi-camera sensor, target detection, saliency detection

Double layer local contrast measure and multi-directional gradient comparison for small infrared target detection 期刊论文 OAI收割
Optik, 2022, 卷号: 258
作者: Ren, Long; Pan, Zhibin; Ni, Yue

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收藏 | 浏览/下载：76/0 | 提交时间：2022/04/02

Infrared (IR) small target detection Double layer local contrast Multi-directional gradient

Infrared dim target detecting algorithm based on multi-feature and spatio-temporal fusion 会议论文 OAI收割
Shanghai, China, 2021-10-28
作者: Bai, Mei; Zhang, Jian; Zhao, Hui

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收藏 | 浏览/下载：42/0 | 提交时间：2022/03/18

Infrared Dim Target Detection TOP-HAT Improved-PM Multi-feature Fusion SCR

Multi-Target Multi-Camera Tracking With Optical-Based Pose Association 期刊论文 OAI收割
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2021, 卷号: 31, 期号: 8, 页码: 3105-3117
作者: You, Sisi; Yao, Hantao; Xu, Changsheng

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收藏 | 浏览/下载：38/0 | 提交时间：2021/11/02

Target tracking Trajectory Cameras Visualization Feature extraction Proposals Object detection Multi-target multi-camera tracking pose estimation optical flow pose matching

Multi-target detection and grasping control for humanoid robot NAO 期刊论文 OAI收割
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2019, 卷号: 33, 期号: 7, 页码: 1225-1237
作者: Zhang, Lei; Zhang, Huayan; Yang, Hanting; Bian, Gui-Bin; Wu, Wanqing

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收藏 | 浏览/下载：74/0 | 提交时间：2019/12/16

grasping method humanoid robot multi-target detection YOLOv3

Multi-target detection method based on variable carrier frequency chirp sequence 期刊论文 OAI收割
SENSORS, 2018, 卷号: 18, 期号: 10, 页码: 1-12
作者: Wang W(王伟); Du JS(杜劲松); Gao J(高洁)

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收藏 | 浏览/下载：68/0 | 提交时间：2018/11/09

Multi-target Detection Continuous Wave Radar Systems Variable Carrier Frequency Chirp Sequence Doppler Ambiguity

ZigBee indoor positioning system precision parameter study based on BP neural network 会议论文 OAI收割
International Conference on Computer, Networks and Communication Engineering (ICCNCE), Beijing, PEOPLES R CHINA, MAY 23-24, 2013
Zeng Wenxiao; Wang Yanen; Wang Meng; Guo Ye

收藏 | 浏览/下载：23/0 | 提交时间：2014/11/10

CC2431 Zigbee location BP Neural Network Euclidian distance centroid algorithm multi-target detection indoor

Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y.

收藏 | 浏览/下载：109/0 | 提交时间：2013/03/25

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Research on tracking approach to low-flying weak small target near the sea (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Xue X.-C.

收藏 | 浏览/下载：32/0 | 提交时间：2013/03/25

Automatic target detection is very difficult in complicate background of sea and sky because of the clutter caused by waves and clouds nearby the sea-level line. In this paper in view of the low-flying target near the sea is always above the sea-level line we can first locate the sea-level line and neglect the image data beneath the sea-level line. Thus the noise under the sea-level line can be suppressed and the executive time of target segmentation is also much reduced. A new method is proposed which first uses neighborhood averaging method to suppress background and enhance targets so as to increase SNR and then uses the multi-point multi-layer vertical Sobel operator combined with linear least squares fitting to locate the sea-level line lastly uses the centroid tracking algorithm to detect and track the target. In the experiment high frame rate and high-resolution digital CCD camera and high performance DSP are applied. Experimental results show that this method can efficiently locate the sea-level line on various conditions of lower contrast and eliminate the negative impact of the clutter caused by waves and clouds and capture and track target real-timely and accurately.