• Journal of Sensor Science and Technology
• /
• v.24 no.1
• /
• pp.54-61
• /
• 2015

In recent years, there has been increasing use of automatic surveillance and monitoring systems based on vision sensors. Humans are often the most important target in the systems, but processing human images is difficult due to the small sizes and flexible motions. Particularly, occlusion among pedestrians in camera images brings practical problems. In this paper, we propose a novel method to separate image regions of occluded pedestrians. A camera equipped with a wide angle lens is attached to the ceiling of a building corridor for sensing pedestrians with a wide field of view. The output images of the camera are processed for the human detection, tracking, identification, distortion correction, and occlusion handling. We resolve the occlusion problem adaptively depending on the angles and positions of their heads. Experimental results showed that the proposed method is more efficient and accurate compared with existing methods.

• Journal of The Korean Ophthalmological Society
• /
• v.59 no.11
• /
• pp.1017-1023
• /
• 2018

Purpose: A recently introduced phacoemulsification system, the WhiteStar $Signature^{(R)}$ PRO, has demonstrated improved nucleus followability and cutting efficiency via an improved pump regulator with a higher reaction response and an automatic occlusion sensing system. In this study, we compared various phacoemulsification parameters between the new system and an older version of the device. Methods: A total of 80 eyes of 68 patients with cataracts who had undergone phacoemulsification by a single surgeon were included in this study. Forty eyes of patients underwent phacoemulsification using the older $Signature^{(R)}$ system (WhiteStar); these patients were classified as the control group. Another 40 eyes of patients underwent phacoemulsification with the newer enhanced system, the WhiteStar $Signature^{(R)}$ PRO; these patients were assigned to the experimental group. During the operation, operative parameters, including the effective phaco time (parameter of effective phaco time with a specific coefficient for the transversal movement expressed in seconds, EFX), ultrasound time (seconds [s]), effective phacoemulsification time (EPT, s), average phacoemulsification power (AVG, %), and balanced salt solution usage, were measured to determine the performance enhancement offered by the updated system. Central corneal thickness was measured before and after surgery to compare corneal edema. The relationships between the two groups were analyzed using an independent t-test. Results: The Signature $PRO^{(R)}$ system showed a lower EFX (p < 0.001), a shorter EPT (p < 0.001), and a smaller AVG (p < 0.001). Postoperative corneal thickness did not differ significantly between the two groups. Conclusions: Comparing the efficacy of the improved reaction speed of the device and automatic occlusion sensing system in performing phacoemulsification, the updated Signature $PRO^{(R)}$ system demonstrated superior followability and cutting efficiency regardless of nuclear cataract hardness.

• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.283-298
• /
• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Korean Journal of Remote Sensing
• /
• v.35 no.3
• /
• pp.457-470
• /
• 2019

Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR) has been attracted attention in the fields of surveillance, reconnaissance, and national security due to its advantage of all-weather and day-and-night imaging capabilities. However, there have been some difficulties in automatically identifying targets in real situation due to various observational and environmental conditions. In this paper, ATR problems in Extended Operating Conditions (EOC) were investigated. In particular, we considered partial occlusions of the target (10% to 50%) and differences in the depression angle between training ($17^{\circ}$) and test data ($30^{\circ}$ and $45^{\circ}$). To simulate various occlusion conditions, SARBake algorithm was applied to Moving and Stationary Target Acquisition and Recognition (MSTAR) images. The ATR accuracies were evaluated by using the template matching and Adaboost algorithms. Experimental results on the depression angle showed that the target identification rate of the two algorithms decreased by more than 30% from the depression angle of $45^{\circ}$ to $30^{\circ}$. The accuracy of template matching was about 75.88% while Adaboost showed better results with an accuracy of about 86.80%. In the case of partial occlusion, the accuracy of template matching decreased significantly even in the slight occlusion (from 95.77% under no occlusion to 52.69% under 10% occlusion). The Adaboost algorithm showed better performance with an accuracy of 85.16% in no occlusion condition and 68.48% in 10% occlusion condition. Even in the 50% occlusion condition, the Adaboost provided an accuracy of 52.48%, which was much higher than the template matching (less than 30% under 50% occlusion).