Theme F "medical robotics for training and guidance": Results and future work

International audienceThis paper presents the projects of the Theme F "medical robotics for training and guidance" inside the GdR STIC-Santé. Three scientific meeting days have been organized during the period 2011-2012. They were devoted to physical simulators of behavior for gesture learning, command of hand prostheses by myoelectric signals or brain activity and the manipulation of objects by the artificial hand, and the last to the use of robots for medical gestures. The next event, scheduled for early 2013, will focus on the evaluation of gesture and especially "evaluation of gesture - to do what?"

Smartphone-based Thermal Imaging System for Diabetic Foot Ulcer Assessment

International audienceThis research work is part of the STANDUP project http://www.standupproject.eu/ dedicated to improve diabetic foot ulcer prevention and treatment of the plantar foot surface using smartphone-embedded thermal imaging system. The aim of this preliminary work is to build an ulcer assessment tool based on a smartphone and an IR thermal camera. The proposed system represents a practical tool for accurate DFU healing assessment, combining color and thermal information in a single user-friendly system. To ensure robust tissue identification, an annotation software was developed based on SLIC superpixel segmentation algorithm. The tool thus developed allows clinicians to achieve objective and accurate tissue identification and annotation. The proposed system could serve as an intelligent telemedicine system to be deployed by clinicians at hospitals and healthcare centers for more accurate diagnosis of diabetic foot ulcers

Specularity Detection Using Time-of-Flight Cameras

Time-of-flight (TOF) cameras are primarily used for range estimation by illuminating the scene through a TOF infrared source. However, additional background sources of illumination of the scene are also captured in the measurement process. This paper exploits conventional Lambertian and Phong's illumination models, developed for 2D CCD image cameras, to propose a radiometric model for a generic TOF camera. The model is used as the basis for a novel specularity detection algorithm. The proposed model is experimentally verified using real data

Automatic Facial Feature Detection for Facial Expression Recognition

International audienceThis paper presents a real-time automatic facial feature point detection method for facial expression recognition. The system is capable of detecting seven facial feature points (eyebrows, pupils, nose, and corners of mouth) in grayscale images extracted from a given video. Extracted feature points then used for facial expression recognition. Neutral, happiness and surprise emotions have been studied on the Bosphorus dataset and tested on FG-NET video dataset using OpenCV. We compared our results with previous studies on this dataset. Our experiments showed that proposed method has the advantage of locating facial feature points automatically and accurately in real-time

Gait-based Gender Classification Considering Resampling and Feature Selection

Two intrinsic data characteristics that arise in many domains are the class imbalance and the high dimensionality, which pose new challenges that should be addressed. When using gait for gender classification, benchmarking public databases and renowned gait representations lead to these two problems, but they have not been jointly studied in depth. This paper is a preliminary study that pursues to investigate the benefits of using several techniques to tackle the aforementioned problems either singly or in combination, and also to evaluate the order of application that leads to the best classification performance. Experimental results show the importance of jointly managing both problems for gait-based gender classification. In particular, it seems that the best strategy consists of applying resampling followed by feature selection

Real-time computational attention model for dynamic scenes analysis: from implementation to evaluation.

International audienceProviding real time analysis of the huge amount of data generated by computer vision algorithms in interactive applications is still an open problem. It promises great advances across a wide variety of elds. When using dynamics scene analysis algorithms for computer vision, a trade-o must be found between the quality of the results expected, and the amount of computer resources allocated for each task. It is usually a design time decision, implemented through the choice of pre-de ned algorithms and parameters. However, this way of doing limits the generality of the system. Using an adaptive vision system provides a more exible solution as its analysis strategy can be changed according to the new information available. As a consequence, such a system requires some kind of guiding mechanism to explore the scene faster and more e ciently. We propose a visual attention system that it adapts its processing according to the interest (or salience) of each element of the dynamic scene. Somewhere in between hierarchical salience based and competitive distributed, we propose a hierarchical yet competitive and non salience based model. Our original approach allows the generation of attentional focus points without the need of neither saliency map nor explicit inhibition of return mechanism. This new real- time computational model is based on a preys / predators system. The use of this kind of dynamical system is justi ed by an adjustable trade-o between nondeterministic attentional behavior and properties of stability, reproducibility and reactiveness

Autonomous Robot For Crack Detection Using Raspberry Pi With IOT & Ultrasonic

Detection of cracks on bridge decks is a vital task for maintaining the structural health and reliability of concrete bridges. Crack inspection is an important task in the maintenance of bridge and it is closely related to structural health of bridge. Currently it is done through a very manual procedure, an experienced human inspector monitors the whole bridge surface visually and try to detect cracks on the bridge and marks the location of crack. But this manual approach having some limitations such limited accuracy. Proposed research focuses on implementing a system having a robot, equipped with a raspberry pi with ultra sonic connectivity with the help of IOT to detect the crack. The robot is travel from start point to end point through an IR sensor. Cracks were identified with the help of ultrasonic waves. Sensor Systems were used for identifying the cracks/holes of a bridge. Raspberry Pi is used as a processor for this robot, which is also best alternative used than the existing one, processing and intimating the manager is done with the help of Raspberry Pi. The information exchange will be done through a simple SMS and geographical location should be done through the Wi-Fi connected to i

Autonomous Recognition System for Barcode Detection in Complex Scenes

Linear barcode technology has been widely used in our common life, such as in logistics, retailed products and many other applications. Many researches and smart applications focus on how to decode the barcode so that it is difficult to locate precisely when the background becomes very complex. Moreover, many smart apps need human interaction to make sure the detected region is in a correct position of the screen. This paper presents an effective approach to locate the barcodes in real-time without manual disturbing. Basic morphological operations and Parallel Line Segment Detector (P-LSD) are applied to achieve the legal block of barcodes. Our method has been evaluated by a standard database and the experimental results show that our approach is more robuster than other earlier methods