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Face recognition and detection processes are used in where need control by camera. During use of face recognition systems appears following problems: can't find face and not enough information in image, changing illumination, occlusion, face shape and etc. In this paper are given current problems and their solving ways.
Technology in devices such as SmartPhones is transforming people's lives. It's also being incorporated into homes in various ways, and hence Smart Environments are becoming more accessible and real. This work focuses on studying and testing a Bayesian Network for anticipating inhabitant interactions with a Smart Environment. It also uses Multi-Agent Systems to model the environment's functionalities...
Despite great progress has been made in recent years, efficient and robust people detection continues to be a challenging problem in the filed of computer vision. In this paper, we propose a highly efficient indoor people detect method based on RGB-D sensor. First, two RGB and depth feature fusing strategies are proposed and compared. Secondly, an improved non-maximum suppression algorithm is proposed...
In order to enhance the classification accuracy of the two-dimensional feature of the image, the idea of a separate classification for each projection direction feature is proposed in this paper. Our method first divides the image into blocks and finds the two-dimensional sub-projection matrix of each sub-block, and then completes the feature extraction by using each column of the projection matrix...
How much does a single image reveal about the environment it was taken in? In this paper, we investigate how much of that information can be retrieved from a foreground object, combined with the background (i.e. the visible part of the environment). Assuming it is not perfectly diffuse, the foreground object acts as a complexly shaped andfar-from-perfect mirror An additional challenge is that its...
Similarity rank lists provide a method for learning generalization of classifiers from examples. Here, we apply it to invariant object recognition and demonstrate that it performs better than other approaches on view and illumination invariant recognition. Recognition from a single view reaches 87% success rate. To study its real world capabilities we introduce subsqare rank matching that works on...
In the past few decades, automatic face recognition has been an important vision task. In this paper, we exploit the spatial relationships of facial local regions by using a novel deep network. In the proposed method, face is spatially scanned with spatial long short-term memory (LSTM) to encode the spatial correlation of facial regions. Moreover, with facial regions of various scales, the complementary...
The major challenges for optical based tracking are the lighting condition, the similarity of the scene, and the position of the camera. This paper demonstrates that under such conditions, the positioning accuracy of Google's Tango platform may deteriorate from fine-grained centimetre level to metre level. The paper proposes a particle filter based approach to fuse the WiFi signal and the magnetic...
Face recognition has gained a great importance in recent years due to the increasing demands of the real-world applications. The modality-independent face recognition also known as heterogeneous face recognition is useful in many applications. Here modality refers to different lighting scenarios in which the picture of the subject is taken. Modality-independent face recognition addresses the issues...
We studied the problem of classifying textured-materials from their single-imaged appearance, under general viewing and illumination conditions, using the theory of random matrices. To evaluate the performance of our algorithm, two distinct databases of images were used: The CUReT database and our database of colorectal polyp images collected from patients undergoing colon capsule endoscopy for early...
The present work proposes to recognize the static hand gestures taken under invariations features as scale, rotation, translation, illumination, noise and background. We use the alphabet of sign language of Peru (LSP). For this purpose, digital image processing techniques are used to eliminate or reduce noise, to improve the contrast under a variant illumination, to separate the hand from the background...
License Plate Detection (LPD) is the pivotal step for License Plate Recognition. In this work, we explore and customize state-of-the-art detection approaches for exclusively handling the LPD in the wild. In-the-wild LPD considers license plates captured in challenging conditions caused by bad weathers, lighting, traffics, and other factors. As conventional methods failed to handle these inevitable...
Material recognition for real-world outdoor surfaces has become increasingly important for computer vision to support its operation in the wild. Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based representations based on internet-mined images of materials captured in the scene...
Night beats with alternating current (AC) illumination. By passively sensing this beat, we reveal new scene information which includes: the type of bulbs in the scene, the phases of the electric grid up to city scale, and the light transport matrix. This information yields unmixing of reflections and semi-reflections, nocturnal high dynamic range, and scene rendering with bulbs not observed during...
The acquisition of partial BRDF measurements using light field cameras and several illumination directions raises critical questions regarding the accuracy of inferences based on that data. Therefore, we attempt to verify the quality of the reconstruction of a full BRDF using partial input data. A dataset that provides a densely sampled BRDF was used, both in viewing and illumination directions. We...
The linear discriminant analysis (LDA) is one of the most efficient supervised dimensionality reduction technique widely used in face recognition. This paper proposed a new weighted LDA to improve the performance of the discriminant analysis. Confusable pair of classes is considered as the primary goal in our objective function. The proposed technique not only improves the minimization of the within-class...
This paper presents a face recognition approach integrated in a simplified system used for profile administration of patients and prosopagnosia applications. The recognition system is based on three successive filters to properly retrieve frontal faces in various illumination conditions and pose variations, a single multi-layer perceptron (MLP) classifier per user and a global comparator of features...
Parking and maneuvering accidents are responsible for a significant amount of real-world — especially property damage — accidents. Insurance research estimates up to 40 % of all claims and up to 30 % of all claim-associated costs around the world are caused by these type of accidents. Therefore, a 360° low speed autonomous emergency braking system could have a high monetary effectiveness. To design...
This paper presents an approach called Gabor-feature-based Local Generic Representation (G-LGR), which take advantages of the sparse representation properties of face recognition in biometric applications. In this work, the main problem is that if only one training subject per class is available. One of the novelties of our new algorithm is to produce virtual samples of each subject; the new sample...
We propose a vision-based method that localizes a ground vehicle using publicly available satellite imagery as the only prior knowledge of the environment. Our approach takes as input a sequence of ground-level images acquired by the vehicle as it navigates, and outputs an estimate of the vehicle's pose relative to a georeferenced satellite image. We overcome the significant viewpoint and appearance...
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