Real-time, long-term hand tracking with unsupervised initialization

This paper proposes a complete tracking system that is capable of long-term, real-time hand tracking with unsupervised initialization and error recovery. Initialization is steered by a three-stage hand detector, combining spatial and temporal information. Hand hypotheses are generated by a random forest detector in the first stage, whereas a simple linear classifier eliminates false positive detections. Resulting detections are tracked by particle filters that gather temporal statistics in order to make a final decision. The detector is scale and rotation invariant, and can detect hands in any pose in unconstrained environments. The resulting discriminative confidence map is combined with a generative particle filter based observation model to enable robust, long-term hand tracking in real-time. The proposed solution is evaluated using several challenging, publicly available datasets, and is shown to clearly outperform other state of the art object tracking methods

Gesture based human-computer interface for 3D design

modeling are amongst the most important fields of interest in current computer vision research. However, traditional hand recognition systems can only operate in constrained environments using coloured gloves or static backgrounds and do not allow for 3D object manipulation. The goal of this research is to develop real-time camera based solutions to control 3D modeling applications using natural hand gestures

Sparse optical flow regularisation for real-time visual tracking

Optical flow can greatly improve the robustness of visual tracking algorithms. While dense optical flow algorithms have various applications, they can not be used for real-time solutions without resorting to GPU calculations. Furthermore, most optical flow algorithms fail in challenging lighting environments due to the violation of the brightness constraint. We propose a simple but effective iterative regularisation scheme for real-time, sparse optical flow algorithms, that is shown to be robust to sudden illumination changes and can handle large displacements. The algorithm proves to outperform well known techniques in real life video sequences, while being much faster to calculate. Our solution increases the robustness of a real-time particle filter based tracking application, consuming only a fraction of the available CPU power. Furthermore, a new and realistic optical flow dataset with annotated ground truth is created and made freely available for research purposes

3D Face tracking and gaze estimation using a monocular camera

Estimating a user’s gaze direction, one of the main novel user interaction technologies, will eventually be used for numerous applications where current methods are becoming less effective. In this paper, a new method is presented for estimating the gaze direction using Canonical Correlation Analysis (CCA), which finds a linear relationship between two datasets defining the face pose and the corresponding facial appearance changes. Afterwards, iris tracking is performed by blob detection using a 4-connected component labeling algorithm. Finally, a gaze vector is calculated based on gathered eye properties. Results obtained from datasets and real-time input confirm the robustness of this metho

Combining wireless and visual tracking for an indoor environment

There has been a lot of research done towards both camera and Wi-Fi tracking respectively, both these techniques have their benefits and drawbacks. By combining these technologies it is possible to eliminate their respective weaknesses, to increase the possibilities of the system as a whole. This is accomplished by fusing the sensor data from Wi-Fi and camera before inserting it in a particle filter. This will result in a more accurate and robust localization system

Mathematische morfologie in de beeldverwerking Mathematical Morphology in Image Processing

Het verwerken van een afbeelding met de computer laat ons toe de kwaliteit van dit beeld te verbeteren, specifieke objecten uit het beeld te segmenteren, of extra informatie tevoorschijn te halen. Mathematische morfologie is een set van wiskundige technieken uit de beeldverwerking die ons toelaat (de vormen in) beelden te analyseren. Dit proefschrift levert oplossingen voor een aantal problemen uit de beeldverwerking, met behulp van mathematische morfologie. Morfologie toepassen op zwart-wit- of grijswaardenbeelden is relatief eenvoudig, maar de theorie uitbreiden voor kleurbeelden stelt een aantal problemen. Aangezien een kleurbeeld veel meer nuttige informatie kan bevatten dan een grijswaardenbeeld, is zo'n uitbreiding wenselijk. We stellen het meerderheidsordeningsschema (MSS) voor, wat ons toelaat kleuren onderling te ordenen op een logische manier. Morfologische beeldverwerking met kleuren wordt dan mogelijk. Een ander onderzoek betreft polymeren en composieten. Deze materialen worden als glijlagers gebruikt in allerhande voorwerpen, zoals huishoudtoestellen, sluizen, poorten, etc. Vandaar dat de studie van de slijtage hiervan belangrijk is. We gaan na of het morfologische patroonspectrum, alsook vergelijkbare technieken, een bijdrage kan leveren aan het wrijvingsonderzoek van dergelijke materialen. Dit zou de snelheid en efficiëntie van de analyses kunnen verbeteren. We merken op dat de spectrale parameters interessante verbanden vertonen met de parameters van de proefopstelling. Het derde luik van de thesis betreft het ontwikkelen van een interpolatietechniek voor zwart-wit-beelden, gebaseerd op mathematische morfologie, genaamd mmINT. Interpolatie is nodig wanneer we wensen in te zoomen op een beeld of de resolutie van het beeld willen vergroten. Dit kan van pas komen wanneer we ingescande of gedownloade tekeningen van slechte kwaliteit (te lage resolutie) willen verbeteren. mmINT werkt aanzienlijk beter dan bestaande methodes. We ontwikkelden ook een snelle variant, mmINTone, en een uitbreiding voor grijswaardenbeelden, mmINTg

A canonical correlation analysis based motion model for probabilistic visual tracking

Particle filters are often used for tracking objects within a scene. As the prediction model of a particle filter is often implemented using basic movement predictions such as random walk, constant velocity or acceleration, these models will usually be incorrect. Therefore, this paper proposes a new approach, based on a Canonical Correlation Analysis (CCA) tracking method which provides an object specific motion model. This model is used to construct a proposal distribution of the prediction model which predicts new states, increasing the robustness of the particle filter. Results confirm an increase in accuracy compared to state-of-the-art method

Corrigendum: Child and adolescent behavior inventory (CABI): A new instrument for epidemiological studies and pre-clinical evaluation

Child and Adolescent Behavior Inventory (CABI): A New Instrument for Epidemiological Studies and Pre-Clinical Evaluation Clinical Practice & Epidemiology in Mental Health, 2013, 9: 51-61 Correction: Few corrections have been provided and replaced online in 15th, 20th, 21st and 22nd rows of the Appendix

DuoStim – a reproducible strategy to obtain more oocytes and competent embryos in a short time-frame aimed at fertility preservation and IVF purposes. A systematic review

Recent evidence suggests that follicular development occurs in a wave-like model during the ovarian cycle, where up to three cohorts of follicles are recruited to complete folliculogenesis. This understanding overtakes the previous dogma stating that follicles grow only during the follicular phase of the menstrual cycle. Therefore, in in vitro fertilization (IVF), novel protocols regarding ovarian stimulation have been theorized based on the use of gonadotrophins to prompt the growth of antral follicles at any stage of the menstrual cycle. These unconventional protocols for ovarian stimulation aim at a more efficient management of poor-prognosis patients, otherwise exposed to conflicting outcomes after conventional approaches. DuoStim appears among these unconventional stimulation protocols as one of the most promising. It combines two consecutive stimulations in the follicular and luteal phases of the same ovarian cycle, aimed at increasing the number of oocytes retrieved and embryos produced in the short time-frame. This protocol has been suggested for the treatment of all conditions requiring a maximal and urgent exploitation of the ovarian reserve, such as oncological patients and poor responders at an advanced maternal age. At present, data from independent studies have outlined the consistency and reproducibility of this approach, which might also reduce the drop-out between consecutive failed IVF cycles in poor-prognosis patients. However, the protocol must be standardized, and more robust studies and cost-benefit analyses are needed to highlight the true clinical pros and cons deriving from DuoStim implementation in IVF