Selection and Evaluation of Color/Depth Camera for Imaging Surgical Stoma

Author(s):  
Michiru Mizoguchi ◽  
Masatoshi Kayaki ◽  
Tomoki Yoshikawa ◽  
Miho Asano ◽  
Katsuhiko Onishi ◽  
...  
Keyword(s):  
Author(s):  
Jun Liu ◽  
Guyue Zhang ◽  
Ye Liu ◽  
Luchao Tian ◽  
Yan Qiu Chen

Author(s):  
Tsanming Ou ◽  
Tomoki Miyamoto ◽  
Yuki Kurosawa ◽  
Takahide Otomo ◽  
Yuko Hoshino ◽  
...  
Keyword(s):  

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Seyed Muhammad Hossein Mousavi ◽  
S. Younes Mirinezhad

AbstractThis study presents a new color-depth based face database gathered from different genders and age ranges from Iranian subjects. Using suitable databases, it is possible to validate and assess available methods in different research fields. This database has application in different fields such as face recognition, age estimation and Facial Expression Recognition and Facial Micro Expressions Recognition. Image databases based on their size and resolution are mostly large. Color images usually consist of three channels namely Red, Green and Blue. But in the last decade, another aspect of image type has emerged, named “depth image”. Depth images are used in calculating range and distance between objects and the sensor. Depending on the depth sensor technology, it is possible to acquire range data differently. Kinect sensor version 2 is capable of acquiring color and depth data simultaneously. Facial expression recognition is an important field in image processing, which has multiple uses from animation to psychology. Currently, there is a few numbers of color-depth (RGB-D) facial micro expressions recognition databases existing. With adding depth data to color data, the accuracy of final recognition will be increased. Due to the shortage of color-depth based facial expression databases and some weakness in available ones, a new and almost perfect RGB-D face database is presented in this paper, covering Middle-Eastern face type. In the validation section, the database will be compared with some famous benchmark face databases. For evaluation, Histogram Oriented Gradients features are extracted, and classification algorithms such as Support Vector Machine, Multi-Layer Neural Network and a deep learning method, called Convolutional Neural Network or are employed. The results are so promising.


Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 51
Author(s):  
Fábio Azevedo ◽  
Jaime S. Cardoso ◽  
André Ferreira ◽  
Tiago Fernandes ◽  
Miguel Moreira ◽  
...  

The usage of unmanned aerial vehicles (UAV) has increased in recent years and new application scenarios have emerged. Some of them involve tasks that require a high degree of autonomy, leading to increasingly complex systems. In order for a robot to be autonomous, it requires appropriate perception sensors that interpret the environment and enable the correct execution of the main task of mobile robotics: navigation. In the case of UAVs, flying at low altitude greatly increases the probability of encountering obstacles, so they need a fast, simple, and robust method of collision avoidance. This work covers the problem of navigation in unknown scenarios by implementing a simple, yet robust, environment-reactive approach. The implementation is done with both CPU and GPU map representations to allow wider coverage of possible applications. This method searches for obstacles that cross a cylindrical safety volume, and selects an escape point from a spiral for avoiding the obstacle. The algorithm is able to successfully navigate in complex scenarios, using both a high and low-power computer, typically found aboard UAVs, relying only on a depth camera with a limited FOV and range. Depending on the configuration, the algorithm can process point clouds at nearly 40 Hz in Jetson Nano, while checking for threats at 10 kHz. Some preliminary tests were conducted with real-world scenarios, showing both the advantages and limitations of CPU and GPU-based methodologies.


2021 ◽  
pp. 115081
Author(s):  
Zahid Halim ◽  
Raja Usman Ahmed Khan ◽  
Muhammad Waqas ◽  
Shanshan Tu
Keyword(s):  

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2736
Author(s):  
Zehao Li ◽  
Shunsuke Yoshimoto ◽  
Akio Yamamoto

This paper proposes a proximity imaging sensor based on a tomographic approach with a low-cost conductive sheet. Particularly, by defining capacitance density, physical proximity information is transformed into electric potential. A novel theoretical model is developed to solve the capacitance density problem using the tomographic approach. Additionally, a prototype is built and tested based on the model, and the system solves an inverse problem for imaging the capacitance density change that indicates the object’s proximity change. In the evaluation test, the prototype reaches an error rate of 10.0–15.8% in horizontal localization at different heights. Finally, a hand-tracking demonstration is carried out, where a position difference of 33.8–46.7 mm between the proposed sensor and depth camera is achieved at 30 fps.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Muhammad Hameed Siddiqi ◽  
Nabil Almashfi ◽  
Amjad Ali ◽  
Madallah Alruwaili ◽  
Yousef Alhwaiti ◽  
...  

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