Clique descriptor of affine invariant regions for robust wide baseline image matching

Assuming that the image distortion between corresponding regions of a stereo pair of images with wide baseline can be approximated as an affine transformation if the regions are reasonably small, recent image matching algorithms have focused on affine invariant region (IR) detection and its description to increase the robustness in matching. However, the distinctiveness of an intensity-based region descriptor tends to deteriorate when an image includes homogeneous texture or repetitive pattern. To address this problem, we investigated the geometry of a local IR cluster (also called a clique) and propose a new clique-based image matching method. In the proposed method, the clique of an IR is estimated by Delaunay triangulation in a local affine frame and the Hausdorff distance is adopted for matching an inexact number of multiple descriptor vectors. We also introduce two adaptively weighted clique distances, where the neighbour distance in a clique is appropriately weighted according to characteristics of the local feature distribution. Experimental results show the clique-based matching method produces more tentative correspondences than variants of the SIFT-based method

Image resolution enhancement using dual-tree complex wavelet transform

In this letter, a complex wavelet-domain image resolution enhancement algorithm based on the estimation of wavelet coefficients is proposed. The method uses a forward and inverse dual-tree complex wavelet transform (DT-CWT) to construct a high-resolution (HR) image from the given low-resolution (LR) image. The HR image is reconstructed from the LR image, together with a set of wavelet coefficients, using the inverse DT-CWT. The set of wavelet coefficients is estimated from the DT-CWT decomposition of the rough estimation of the HR image. Results are presented and discussed on very HR QuickBird data, through comparisons between state-of-the-art resolution enhancement methods

Gait recognition and understanding based on hierarchical temporal memory using 3D gait semantic folding

Gait recognition and understanding systems have shown a wide-ranging application prospect. However, their use of unstructured data from image and video has affected their performance, e.g., they are easily influenced by multi-views, occlusion, clothes, and object carrying conditions. This paper addresses these problems using a realistic 3-dimensional (3D) human structural data and sequential pattern learning framework with top-down attention modulating mechanism based on Hierarchical Temporal Memory (HTM). First, an accurate 2-dimensional (2D) to 3D human body pose and shape semantic parameters estimation method is proposed, which exploits the advantages of an instance-level body parsing model and a virtual dressing method. Second, by using gait semantic folding, the estimated body parameters are encoded using a sparse 2D matrix to construct the structural gait semantic image. In order to achieve time-based gait recognition, an HTM Network is constructed to obtain the sequence-level gait sparse distribution representations (SL-GSDRs). A top-down attention mechanism is introduced to deal with various conditions including multi-views by refining the SL-GSDRs, according to prior knowledge. The proposed gait learning model not only aids gait recognition tasks to overcome the difficulties in real application scenarios but also provides the structured gait semantic images for visual cognition. Experimental analyses on CMU MoBo, CASIA B, TUM-IITKGP, and KY4D datasets show a significant performance gain in terms of accuracy and robustness

Multi-set canonical correlation analysis for 3D abnormal gait behaviour recognition based on virtual sample generation

Small sample dataset and two-dimensional (2D) approach are challenges to vision-based abnormal gait behaviour recognition (AGBR). The lack of three-dimensional (3D) structure of the human body causes 2D based methods to be limited in abnormal gait virtual sample generation (VSG). In this paper, 3D AGBR based on VSG and multi-set canonical correlation analysis (3D-AGRBMCCA) is proposed. First, the unstructured point cloud data of gait are obtained by using a structured light sensor. A 3D parametric body model is then deformed to fit the point cloud data, both in shape and posture. The features of point cloud data are then converted to a high-level structured representation of the body. The parametric body model is used for VSG based on the estimated body pose and shape data. Symmetry virtual samples, pose-perturbation virtual samples and various body-shape virtual samples with multi-views are generated to extend the training samples. The spatial-temporal features of the abnormal gait behaviour from different views, body pose and shape parameters are then extracted by convolutional neural network based Long Short-Term Memory model network. These are projected onto a uniform pattern space using deep learning based multi-set canonical correlation analysis. Experiments on four publicly available datasets show the proposed system performs well under various conditions

Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors

This paper presents a gait recognition method which combines spatio-temporal motion characteristics, statistical and physical parameters (referred to as STM-SPP) of a human subject for its classification by analysing shape of the subject's silhouette contours using Procrustes shape analysis (PSA) and elliptic Fourier descriptors (EFDs). STM-SPP uses spatio-temporal gait characteristics and physical parameters of human body to resolve similar dissimilarity scores between probe and gallery sequences obtained by PSA. A part-based shape analysis using EFDs is also introduced to achieve robustness against carrying conditions. The classification results by PSA and EFDs are combined, resolving tie in ranking using contour matching based on Hu moments. Experimental results show STM-SPP outperforms several silhouette-based gait recognition methods

PERNIKAHAN SEMARGA DALAM KOMUNITAS TIONGHOA PERANAKAN DI BANDUNG PADA AWAL ABAD KE 20 - KASUS KELUARGA TAN SIM TJONG (MARRIAGE WITHIN A CLAN IN CHINESE SOCIETY IN BANDUNG DURING THE EARLY 20TH CENTURY– CASE OF TAN SIM TJONG´S FAMILY)

Abstrak Pernikahan Semarga yang terjadi dalam kalangan masyarakat Tionghoa di Bandung pada awal abad ke 20 telah mengundang konflik budaya dan sekaligus membuka paradigma baru berupa kebebasan individu dalam memilih pasangannya tanpa batasan nama marga. Polarisasi pandangan dan tindakan terjadi dalam kedua keluarga bermarga Tan yang mencerminkan situasi masyarakat Bandung saat itu. Hal ini dibukukan dalam novel „Rasia Bandoeng“ yang diterbitkan 1918. Novel ini merupakan cerita nyata keluarga Tan Sim Tjong yang antara lain membahas konflik yang terjadi akibat pelanggaran adat pernikahan Tionghoa saat itu. Masyarakat Bandung mengenal Tan Sim Tjong sebagai nama Gang Simtjong dikawasan Citepus Bandung. Melalui pendekatan historis deskriptif, sosok dan jejak Tan Sim Tjong serta dukungannya dalam konteks pernikahan semarga dibahas secara terperinci dalam tulisan ini, dengan harapan karya ini bisa menggambarkan kearifan lokal dan mengisi perkembangan sejarah kota Bandung. Kata kunci: Tan Sim Tjong, Pernikahan Semarga, Hermine, Tionghoa Peranakan, Rasia Bandoeng Abstract Marriage within a clan took place in Chinese society in Bandung during the early 20th Century. It caused culture conflict, but at the same time created a new paradigm for individual freedom when people choice theirs partner without consideration to the family name. The polarity of ideas and their translation into action was typified by the intermarriage between two Tan families. The story of this was published in 1918 in a novel entitled “Rasia Bandoeng” (“The Secret of Bandoeng”). This novel tells the real story of Tan Sim Tjong’s family and deals with the conflicts arising from marrying within the same surname group, which was forbidden in the Chinese culture of that period. The people in Bandung know Tan Sim Tjong as Simtjong Alley in the Citepus district of Bandung. The paper takes a historical approach and gives detailed information about Tan Sim Tjong, his heritage and his support for the relationships and marriage within a clan, in order to maintain the local wisdom and the historical development in Bandung. Keywords: Tan Sim Tjong, Marriage within a Clan, Hermine, Chinese “Peranakan”, Rasia Bandoen

2.5D multi-view gait recognition based on point cloud registration

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM

Hubungan Sistem Manajemen Risiko dengan Ketidakpastian Lingkungan dan Strategi Serta Dampaknya terhadap Kinerja Organisasi

Good Corporate Governance (GCG) practices demand management to formulate and implementa sound risk management to ensure that all possible future negative events have been managedproperly. Theoretically, risk is affected by the strategy that is formulated and implemented bymanagement to achieve high performance. Risk is also affected by the degree of environmentuncertainty faced by each organization.This study focused on the moderating effect of business strategy orientation and environmentuncertainty on organization's performance. Questionnaires were sent to 127 state-owned enterprisesand 413 companies listed in the Indonesia Stock Exchange. Response rate was about 12%.Result of the study showed that environment uncertainty did not have a moderating effect on therelationship between risk management system and organization's performance. Furthermore, resultof this study also showed that strategy did have a moderating effect on the relationship between riskmanagement system and organization's performance.Key words: good corporate governance, risk management system, strategy, environment uncertainty,organization's performance