Descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device
Visual recognition and vision based retrieval of objects from large databases are tasks with a wide spectrum of potential applications. In this paper we propose a novel recognition method from video sequences suitable for retrieval from databases acquired in highly unconstrained conditions e.g. using a mobile consumer-level device such as a phone. On the lowest level, we represent each sequence as a 3D mesh of densely packed local appearance descriptors. While image plane geometry is captured implicitly by a large overlap of neighbouring regions from which the descriptors are extracted, 3D information is extracted by means of a descriptor transition table, learnt from a single sequence for each known gallery object. These allow us to connect local descriptors along the 3rd dimension (which corresponds to viewpoint changes), thus resulting in a set of variable length Markov chains for each video. The matching of two sets of such chains is formulated as a statistical hypothesis test, whereby a subset of each is chosen to maximize the likelihood that the corresponding video sequences show the same object. The effectiveness of the proposed algorithm is empirically evaluated on the Amsterdam Library of Object Images and a new highly challenging video data set acquired using a mobile phone. On both data sets our method is shown to be successful in recognition in the presence of background clutter and large viewpoint changes.
Code (0)
등록된 구현이 없습니다.
Tasks
ObjectRetrievalSimilar Papers 제목 키워드 기반
R-Theta Local Neighborhood Pattern for Unconstrained Facial Image Recognition and Retrieval
In this paper R-Theta Local Neighborhood Pattern (RTLNP) is proposed for facial image retrieval. RTLNP exploits relationships amongst the pixels in local neighborhood of the reference pixel at different angular and radia…
Face Image RetrievalImage RetrievalRetrievalSupScene: Scene-Structured Overlap Supervision for Image Retrieval in Unconstrained SfM
Image retrieval is a critical step for reducing the quadratic cost of image matching in unconstrained Structure-from-Motion (SfM). Unlike generic image retrieval, however, the relevant goal of SfM is to identify geometri…
Image RetrievalImage MatchingLocal Quadruple Pattern: A Novel Descriptor for Facial Image Recognition and Retrieval
In this paper a novel hand crafted local quadruple pattern (LQPAT) is proposed for facial image recognition and retrieval. Most of the existing hand-crafted descriptors encodes only a limited number of pixels in the loca…
RetrievalLocal Directional Relation Pattern for Unconstrained and Robust Face Retrieval
Face recognition is still a very demanding area of research. This problem becomes more challenging in unconstrained environment and in the presence of several variations like pose, illumination, expression, etc. Local de…
Face RecognitionImage RetrievalRelationRetrievalCentre Symmetric Quadruple Pattern: A Novel Descriptor for Facial Image Recognition and Retrieval
Facial features are defined as the local relationships that exist amongst the pixels of a facial image. Hand-crafted descriptors identify the relationships of the pixels in the local neighbourhood defined by the kernel. …
Retrieval