Automatic learning of gait signatures for people identification

This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (i.e. optical flow components). We carry out a thorough experimental evaluation of the proposed CNN architecture on the challenging TUM-GAID dataset. The experimental results indicate that using spatio-temporal cuboids of optical flow as input data for CNN allows to obtain state-of-the-art results on the gait task with an image resolution eight times lower than the previously reported results (i.e. 80x60 pixels).Comment: Proof of concept paper. Technical report on the use of ConvNets (CNN) for gait recognition. Data and code: http://www.uco.es/~in1majim/research/cnngaitof.htm

Evaluation of CNN architectures for gait recognition based on optical flow maps

This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Fisher Motion Descriptor for Multiview Gait Recognition

The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to de ne custom spatial con gurations of the descriptors around the target person, obtaining a rich representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor [1]) extracted on the di erent spatial areas of the person are combined into a single high-level gait descriptor by using the Fisher Vector encoding [2]. The proposed approach, coined Pyramidal Fisher Motion, is experimentally validated on `CASIA' dataset [3] (parts B and C), `TUM GAID' dataset [4], `CMU MoBo' dataset [5] and the recent `AVA Multiview Gait' dataset [6]. The results show that this new approach achieves state-of-the-art results in the problem of gait recognition, allowing to recognize walking people from diverse viewpoints on single and multiple camera setups, wearing di erent clothes, carrying bags, walking at diverse speeds and not limited to straight walking paths

Parallelization of an algorithm for the automatic detection of deformable objects

This work presents the parallelization of an algorithm for the detection of deformable objects in digital images. The parallelization has been implemented with the message passing paradigm, using a master-slave model. Two versions have been developed, with synchronous and asynchronous communications

Use of camera trapping in determining Iberian lynx population parameters: The use area and its limitations

Below are the results of the survey of the Iberian lynx obtained with camera-trapping between 2000 and 2007 in Sierra Morena. Two very important aspects of camera-trapping concerning its efficiency are also analyzed. The first is the evolution along years according to the camera-trapping type used of two efficiency indicators. The results obtained demonstrate that the most efficient lure is rabbit, though it is the less proven (92 trap-nights), followed by camera-trapping in the most frequent marking places (latrines). And, we propose as a novel the concept of use area as a spatial reference unit for the camera-trapping monitoring of non radio-marked animals is proposed, and its validity discussed

Treatment with implants in patients with diabetes. A 7-year comparative study

Introducción. La implantología oral puede constituir una modalidad terapéutica en el tratamiento prostodóncico de los pacientes con compromiso médico. El estudio muestra la evaluación del tratamiento con implantes en pacientes con diabetes comparados con pacientes sin diabetes. Métodos. 48 pacientes edéntulos totales (24 pacientes diabéticos y 24 no diabéticos) fueron tratados con 96 implan- tes con superficie arenada y grabada Galimplant ® en la mandíbula para su rehabilitación prostodóncica con sobre- dentaduras mandibulares. 2 implantes fueron insertados en cada paciente. Los implantes fueron cargados funcional- mente tras un periodo de tiempo de 6 semanas con retenedores de fricción. Los hallazgos clínicos (implantológicos y prostodóncicos) se han seguido durante 7 años. Resultados. Los resultados indican una supervivencia de los implantes del 95,8%. Durante el periodo de seguimeinto clínico se perdieron 4 implantes (dos implantes en cada grupo). La pérdida de hueso marginal media fué de 0,7 mm en ambos grupos. El 100% de los pacientes fueron tratados mediante una sobredentadura implantorretenida con anclajes de fricción. En 14 pacientes se realizaron cambios en los componentes plásticos de los ataches. El seguimiento clínico medio fue de 82,5 meses (60-102 meses). Conclusiones. Los resultados del presente estudio indican que el tratamiento con implantes dentales en pacientes diabéticos es una terapéutica exitosa sin diferencias entre los pacientes diabéticos y no diabéticos. PALABRAS CLAVE: Implantes dentales, pacientes geriátricos, diabetes mellitus, sobredentaduras, oseo- integración, implantología oral.Introduction. Implant dentistry can to constitute a therapeutic modality in the prosthodontic treatment of medically compromised patients. This study reports the evaluation of treatment with implants in patients with diabetes compared with patients without diabetes. Methods. 48 edentulous patients (24 diabetic patients and 24 non-diabetic patients) were treated with 96 Galimplant ® sand-blasted and acid-etched surface implants for prosthodontic rehabilitation with mandibular overdentures. Two implants were inserted in each patient. Implants were loaded after a healing free-loading period between 6 weeks with locator attaches. Clinical findings (implant and prosthodontics) were followed during at 7 years. Results. Clinical results indicate a survival rate of implants of 95.8% in both groups. Four implant was lost during the follow-up period (two implants in each group). Media marginal bone loss was 0.7 mm in both groups. 100% of patients were treated with overdentures retained with 2 implants with locator attaches. Changes in plastic components of attaches were reported in 14 patients. The media follow-up was of 82.5 months (60-102 months). Conclusions. Clinical results of this study indicate that treatment with dental implants in diabetic patients is a successful implant treatment without differences with nondiabetic patients