Optical flow segmentation for pedestrian detection

This project will study the motion between consecutive frames in a video in order to segment meaningful regions. In particular, video recorded from a camera on top of a car will be used to analyse the pedestrian moving around it. This information could potentially be used to alert the driver of possible obstacles.Pedestrian detection has become an active area of research in recent years. It is widely applied in different applications such as surveillance systems, automotive safety or robotics among others. The current project aims to localize moving objects on sequences of images, focusing on pedestrian detection. First, the apparent motion in the scene will be computed. Afterward motion vectors will be divided into moving objects or background and finally, the resulting segments will be analysed by introducing them into a classifier in order to determine if they are pedestrians or not.La detección de peatones se ha convertido en un área de investigación muy activa en los últimos años. Se aplica en una gran variedad de aplicaciones, como por ejemplo en sistema de vigilancia, seguridad en automóviles o en la robótica, entre otros. Este proyecto pretende localizar objetos en movimiento en secuencias de imágenes, centrando la atención en la detección de peatones. Primeramente, se calculará el movimiento aparente en la escena, a continuación, los vectores de movimiento se dividirán entre objetos móviles y fondo, y finalmente, las segmentaciones obtenidas serán analizadas introduciéndolas en un clasificador, para determinar si se trata de peatones o no. La detecció de vianants s’ha convertit en una àrea d’investigació molt activa en els darrers anys. S’aplica a una gran varietat d’aplicacions com per exemple en sistemes de vigilància, seguretat en automòbils o en la robòtica, entre d’altres. Aquest projecte pretén localitzar objectes en moviment en seqüències d’imatges, centrant-ne l’atenció en la detecció de vianants. Primerament, es calcularà el moviment aparent en l’escena, a continuació, els vectors de moviment es dividiran entre objectes mòbils o en fons estàtic, i finalment, els segments obtinguts seran analitzats introduint-los en un classificador, per tal de determinar si es tracta de vianants o no

Recovering articulated non-rigid shapes, motions and kinematic chains from video

Recovering articulated shape and motion, especially human body motion, from video is a challenging problem with a wide range of applications in medical study, sport analysis and animation, etc. Previous work on articulated motion recovery generally requires prior knowledge of the kinematic chain and usually does not concern the recovery of the articulated shape. The non-rigidity of some articulated part, e.g. human body motion with non-rigid facial motion, is completely ignored. We propose a factorization-based approach to recover the shape, motion and kinematic chain of an articulated object with non-rigid parts altogether directly from video sequences under a unified framework. The proposed approach is based on our modeling of the articulated non-rigid motion as a set of intersecting motion subspaces. A motion subspace is the linear subspace of the trajectories of an object. It can model a rigid or non-rigid motion. The intersection of two motion subspaces of linked parts models the motion of an articulated joint or axis. Our approach consists of algorithms for motion segmentation, kinematic chain building, and shape recovery. It is robust to outliers and can be automated. We test our approach through synthetic and real experiments and demonstrate how to recover articulated structure with non-rigid parts via a single-view camera without prior knowledge of its kinematic chain