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In this paper, we present methods for the reconstruction of 3D histological volumes of the human hippocampal formation from histology slices. Inter-slice alignment is guided by a graph-theoretic approach that minimizes the impact of badly distorted slices. The reconstruction is refined by iterative affine and deformable co-registration with a high-resolution MRI of the postmortem tissue sample. We...
This research presents a 3-D human arms tracking method with a monocular camera. In our previous work, multiple clues have been integrated by the multiple importance sampling particle filter to track the arms with arbitrary motion on the images. Due to the lack of depth information when using a monocular camera, an online sequential pose estimation based on the structure-from-motion is proposed here...
Human action recognition and interpretation constitutes an important part of the video understanding. In this work, a novel action recognition system is developed that uses edge features obtained from optical flow power shapes which is represented as sequential gradient histograms. The presented system can achieve equal results to the complicated top action recognition systems of nowadays. The system...
In this study, a system is developed to measure intensity of human essential tremor in a qualitative manner. The system has a ring shape and contains a three-axis accelerometer, microcontroller and memory unit. Three-axis acceleration data is sampled at 30Hz and stored in 256Mbit flash memory. The system is able to run along one day using single 1000mAh capacity 3V battery. The data collected is transferred...
Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic...
Human age estimation based on face images can figure in a wide variety of real-world applications. In this paper, we propose a novel and efficient facial age estimation algorithm which decides human age in a hierarchical framework. Biologically, human lives can be roughly divided into two stages, the period from birth to adulthood and the period from adulthood to old age, which are quite different...
In this paper, we use a segmentation method applied to the plants images analysis. The segmentation gives groups of pixels, and we propose to use merging operators to address the most relevant groups in order to improve the recognitions systems performance. In particular, we use an operator called fully reinforced. The experiments carried out show that the use of improves outcomes for structuring...
An innovative way of object shape representation using Density Histogram of Feature Points (DHFP) is introduced and used in this paper. We have named this method Enhanced Density Histogram of Feature Points (EDHFP). We use silhouette images where the image region ξ consists of only those pixels that correspond to points on the object and have a value one (1) indicating “on” pixels. We count the number...
Swift lets are birds contained within the four genera Aerodramus, Hydrochous, Schoutedenapus and Collocalia. To date, the bird nest grading is based on weight, shape and size. The inspection and grading for raw edible bird nest were performed visually by expert panels. This conventional method is relying more on human judgments. A Fourier-based shape separation (FD) method was developed from Charge...
Analysis of composite shapes recently receives increasing amount of research attention. Different from a silhouette, a composite shape rarely contains a complete envelope. In the paper, we propose a novel envelope extraction algorithm based on the Delaunay triangulation for composite shapes. By analyzing the spatial relationship among individual components of contours and their concavities, we establish...
This paper proposes a novel technique for 3-D recovery of a non-rigid object, such as a human in motion, from a single camera view. To achieve the 3-D recovery, the proposed technique performs segmentation of an object under deformation into respective parts which are regarded as rigid. For high accuracy segmentation, multi-stage learning and local subspace affinity are employed in this stage. Each...
We propose a high-accuracy human detection method featuring a Haar-like filter expressing the human shape and using depth information obtained by capturing people from above with a time-of-flight (TOF) camera. This method extracts object regions by performing background subtraction against this depth information, and passes these extracted object regions through a Haar-like filter based on a human...
The detection of salient regions from mesh surfaces is an important preprocessing step for many 3D applications, such as mesh simplification, registration, segmentation and compression, etc. The detected salient regions can facilitate the understanding of the structure and finding the regions/components that are important on 3D surfaces. This paper proposes a novel method for saliency detection by...
Due to the high degree of freedom found in hand motion, it is difficult to model articulated hand configurations. In addition, observed hand shapes vary according to the hand rotation, even when using the same hand configuration. This paper presents a new manifold embedding method for modeling low dimensional hand configurations and hand rotation using a 4D torus manifold, in which the product of...
We propose a method for estimating 3-D hand postures from 2-D monocular images in real-time. The estimation is based on finding the best matched posture from typical postures whose appearances are learned in advance. For high accuracy, conventional methods require high computational cost for comparing an input with many typical postures. In our method, a tree is automatically generated and trained...
We present a novel motion descriptor for gesture recognition based on depth camera. Since each object motion leads to a specific depth change characterized by depth difference, we can recognize object motion via Depth Difference Distribution (DDD) in object region. The DDD is approximated by DDD descriptor in three steps. First, each pixel's depth difference value is quantified into Depth Difference...
In gait recognition field, template-based approaches such as Gait Energy Image (GEI) and Chrono-Gait Image (CGI) can achieve good recognition performance with low computational cost. Meanwhile, CGI can preserve temporal information better than GEI. However, they pay less attention to the local shape features. To preserve temporal information and generate more abundant local shape features, we generate...
Recognizing collective human activities has gained attention. Collective activities are such as queueing in a line, talking together and waiting by an intersection. It is often hard to differentiate between these activities only by the appearance of the individual. Hence, recent works exploit the contextual information of other people nearby. However, these works do not take enough care of the spacial...
Finding correspondences between two 3D shapes is common both in computer vision and computer graphics. In this paper, we propose a general framework that shows how to build correspondences by utilizing the isometric property. We show that the problem of finding such correspondences can be reduced to the problem of spectral assignment, which can be solved by finding the principal eigenvector of the...
This paper introduces a vision-based motion capture system. Motion capturing technology consists of two categories: model-based tracking and example-based indexing. The motion capturing systems face two challenges: parameter estimation in high-dimensional space and self-occlusion. Our algorithm extends the locality sensitive hashing (LSH) method to find the approximate examples and then estimates...
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