Guangbing Xiao^*, Ruijie Gu, Ning Sun, Yong Zhang

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1329-1348, 2024, DOI:10.32604/csse.2024.050817 - 13 September 2024

Abstract In response to the challenges posed by insufficient real-time performance and suboptimal matching accuracy of traditional feature matching algorithms within automotive panoramic surround view systems, this paper has proposed a high-performance dimension reduction parallel matching algorithm that integrates Principal Component Analysis (PCA) and Dual-Heap Filtering (DHF). The algorithm employs PCA to map the feature points into the lower-dimensional space and employs the square of Euclidean distance for feature matching, which significantly reduces computational complexity. To ensure the accuracy of feature matching, the algorithm utilizes Dual-Heap Filtering to filter and refine matched point pairs. To further More >

Chang Zhao¹, Wei Sun^1,3,*, Xiaorui Zhang^2,3, Xiaozheng He⁴, Jun Zuo¹, Wei Zhao¹

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1083-1094, 2023, DOI:10.32604/csse.2023.032786 - 03 November 2022

Abstract The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion, which leads to a false matching, with an inaccurate pose estimation or failed tracking. To address the challenge above, a new method of feature point matching is proposed in this paper, which combines the variable velocity model with the reverse optical flow method. First, the constant velocity model is extended to a new variable velocity model, and the expanded variable velocity model is used to provide… More >

Lihua Zhu¹, Yan Zhang¹, Yu Wang^1,*, Cheire Cheng²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 593-609, 2022, DOI:10.32604/cmc.2022.022053 - 03 November 2021

Abstract In nowadays society, the safety of the elderly population is becoming a pressing concern, especially for those who live alone. There might be daily risks such as accidental falling or treatment attack on them. Aiming at these problems, indoor positioning could be a critical way to monitor their states. With the rapidly development of the imaging techniques, wearable and portable cameras are very popular, which could be set on human individual. And in view of the advantages of the visual positioning, the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor.… More >

Chandrasekar Thaventhiran, K. R. Sekar^*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 495-506, 2022, DOI:10.32604/iasc.2022.019546 - 03 September 2021

Abstract Prediction of lung cancer at early stages is essential for diagnosing and prescribing the correct treatment. With the continuous development of medical data in healthcare services, Lung cancer prediction is the most concerning area of interest. Therefore, early prediction of cancer helps in reducing the mortality rate of humans. The existing techniques are time-consuming and have very low accuracy. The proposed work introduces a novel technique called Target Projection Feature Matched Deep Artificial Neural Network with LSTM (TPFMDANN-LSTM) for accurate lung cancer prediction with minimum time consumption. The proposed deep learning model consists of multiple… More >

Rong Duan¹, Junshan Tan^{1, *}, Jiaohua Qin¹, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2335-2350, 2020, DOI:10.32604/cmc.2020.012161 - 16 September 2020

Abstract In recent years, with the massive growth of image data, how to match the image required by users quickly and efficiently becomes a challenge. Compared with single-view feature, multi-view feature is more accurate to describe image information. The advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image retrieval. In this paper, a hash algorithm of multi-index image retrieval based on multi-view feature coding is proposed. By learning the data correlation between different views, this algorithm uses multi-view data with deeper level image More >