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In this paper, we propose a patched-based deep Boltzmann shape priors for visual tracking. The shape priors are generated from deep Boltzmann machine network. The network consists of three layers of hidden and visible units. The generated shapes not only maintain general shapes from a variety of poses, but also entail local modifications with high probability.
We propose a combinatorial solution for the problem of non-rigidly matching a 3D shape to 3D image data. To this end, we model the shape as a triangular mesh and allow each triangle of this mesh to be rigidly transformed to achieve a suitable matching to the image. By penalising the distance and the relative rotation between neighbouring triangles our matching compromises between the image and the...
Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches...
Background Subtraction is the major important step in many image processing applications which can be applied in much of video surveillances. The major result of this method is accuracy as well as processing time. So we mainly focused on these two challenges. We parallelized the Two Layered CodeBook Model on Graphical Processing Unit (GPU) for increasing the processing speed and the accuracy of the...
Colour, texture, shape, and relative position descriptors are fundamental visual descriptors. In particular, a relative position descriptor is a quantitative representation of the relative position of two spatial objects, and a basis from which models of spatial relationships (like inside, above, around, near) can be derived. The affine properties of visual descriptors have been the subject of much...
Photometric ambient occlusion estimation is to recover the local visibility of a scene from multiple illuminations at a fixed viewpoint. Its effectiveness is highly dependent on the amount of illuminations. In this paper, we study how to reliably extract photometric ambient occlusion from sparsely sampled illuminations. We specifically propose an effective relative entropy minimization framework to...
Researchers gave the vehicle and pedestrian detection lots of attention to alarm the drivers for improving the safety of transportation systems. However, bicycles are also the significant factor of the safety on road. In this paper, a bicycle detector for side-view image is proposed based on the observation that a bicycle consists of two wheels in the form of ellipse shapes and a frame in the form...
We propose a new categorical object recognition algorithm robust to scale changes. We first partition an input image into k regions by using depth data from an RGB-D sensor, and then we estimate the object scale for each partitioned region. Finally, scaled model is applied to recognize the object.
This paper presents a sonification model to convert object tracking information into sound in real time. The goal is to generate a sound that describes the information given by a trajectory - such as position, direction, velocity and shape - to help visually impaired people to "see" the world: how can we describe to them a square like we do by drawing it in a sheet of paper? The usage can...
Vehicle classification system is an important part of intelligent transportation system (ITS), which can provide us the necessary information for autonomous navigation, toll systems, surveillance and security systems, and transport planning. In this paper, we introduce a vehicle classification system based on dynamic Bayesian network (DBN). Three main types of features are employed in our system:...
In this paper, we present a novel generalized Segment-Forest Model (SFM) to segment an object as well as label all the object's semantic parts simultaneously. Segment-Forest is composed by various generated segment trees that act directly on super pixels. Unlike recent works, SFM does not need the prior information like skeleton to capture the core structure of an object, but actively learns the structure...
In this paper, we present a pedestrian tracking system by using image segmentation algorithm, which incorporated pedestrian shape prior into Random Walks segmentation [1] from a static image, and tracking people by Connected Component Labeling Algorithm. We improve the random walks segmentation algorithm by using prior shape information, which provides appropriate seeds for the pedestrian segmentation...
3D object recognition from 3D scenes, is one of the challenges of several researchers in the field of computer vision, engineering and Robotics. The occlusion is one of the problems that we can found. One of the possible solutions in this situation is to find a part of an object in the scene that can be identified. For this reason, we are mainly interested to partial shape retrieval methods. In this...
In this paper, a novel approach is proposed for shape classification based on the semi-supervised framework. For shape similarity-measuring problem, in order to avoid solving an NP problem produced by finding some affine transformation and to enhance its robustness for local changes of the shapes, we switch to compute an energy index defined by the degree of segmentation. The corresponding segmentation...
In computer vision extracting an object from an image automatically is too hard. Towards addressing this issue a comprehensive analysis of most of the Object detection through different Segmentations is performed taken from the major recent publications covering various aspects of the research in this area. We identify the following methods of the state-of-the-art techniques in which an object can...
We address the problem of joint detection and segmentation of multiple object instances in an image, a key step towards scene understanding. Inspired by data-driven methods, we propose an exemplar-based approach to the task of multi-instance segmentation using a small set of annotated reference images. We design a novel CRF model that jointly models object appearance, shape deformation, and object...
This paper extends the bag-of-visual-words representations to a bag-of-visual-phrases model. The introduced bag-of-visual-phrases representation is constructed upon a proposed method for probabilistic description of co-occurring visual words, which is adapted for each reference word. This bag-of-visual-phrases representation implicitly encodes spatial relationships among visual words, thus being a...
A new algorithm for fast contour alignment of digital images is presented. The algorithm is based on a filterbank approach in conjunction with a closed-form solution procedure for least-squares subproblems involved. Simulation results are presented, which demonstrate that the proposed algorithm achieves globally optimal solution and requires a computational complexity of O(N log N) compared to the...
In this paper, a new approach is proposed for modeling and indexing outline shapes by using simple primitives extracted from the contours of objects. We also propose a new and an efficient way to index the outline shapes. Indexes are issued from characteristic polygons determined on the outline shapes of the objects. Despite the recognition process is not the aim of our method, the proposed indexing...
Gesture interaction by gait is becoming a topic of interest in human computer interaction due to its advantage of identifying individuals. This paper provides a brief review of recent developments on gait tracking and gives an overview of model-based approaches for gesture recognition. To recognize gait gesture in real-time, model-based approach is generally used in gesture interaction. The camera...
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