Learning optimised representations for view-invariant gait recognition

Gait recognition can be performed without subject cooperation under harsh conditions, thus it is an important tool in forensic gait analysis, security control, and other commercial applications. One critical issue that prevents gait recognition systems from being widely accepted is the performance drop when the camera viewpoint varies between the registered templates and the query data. In this paper, we explore the potential of combining feature optimisers and representations learned by convolutional neural networks (CNN) to achieve efficient view-invariant gait recognition. The experimental results indicate that CNN learns highly discriminative representations across moderate view variations, and these representations can be further improved using view-invariant feature selectors, achieving a high matching accuracy across views

Diazido­bis­[4,4,5,5-tetra­methyl-2-(1,3-thia­zol-2-yl)-2-imidazoline-1-oxyl 3-oxide-κ2 N 1,O 3]nickel(II)

In the title compound, [Ni(N3)2(C10H14N3O2S)2], the NiII atom lies on an inversion center and adopts a distorted trans-NiO2N4 octa­hedral geometry, coordinated by two N,O-bidentate 4,4,5,5-tetra­methyl-2-(5-methyl­imidazol-4-yl)-2-imidazoline-1-oxyl 3-oxide nitronyl nitroxide radical ligands and two monodentate azide anions

On reducing the effect of silhouette quality on Iindividual gait recognition : a feature fusion approach

The quality of the extracted gait silhouettes can hinder the performance and practicability of gait recognition algorithms. In this paper, we propose a framework that integrates a feature fusion approach to improve recognition rate under this situation. Specifically, we first generate a dataset containing gait silhouettes with various qualities based on the CASIA Dataset B. We then fuse gallery data with different qualities and project data into embedded subspaces.We perform classification based on the Euclidean distances between fused gallery features and probe features. Experimental results show that the proposed framework can provide important improvements on recognition rate

The influence of segmentation on individual gait recognition

The quality of the extracted gait silhouettes can hinder the performance and practicability of gait recognition algorithms. In this paper, we analyse the influence of silhouette quality caused by segmentation disparities, and propose a feature fusion strategy to improve recognition accuracy. Specifically, we first generate a dataset containing gait silhouette with various qualities generated by different segmentation algorithms, based on the CASIA Dataset B. We then project data into an embedded subspace, and fuse gallery features of different quality levels. To this end, we propose a fusion strategy based on Least Square QR-decomposition method. We perform classification based on the Euclidean distance between fused gallery features and probe features. Evaluation results show that the proposed fusion strategy attains important improvements on recognition accuracy

Extracting Keyphrases from Chinese News Articles Using TextRank and Query Log Knowledge

PACLIC 23 / City University of Hong Kong / 3-5 December 200

Effective Tag Set Selection in Chinese Word Segmentation via Conditional Random Field Modeling

PACLIC 20 / Wuhan, China / 1-3 November, 200

Amphibians and Reptiles of Dinghushan in Guangdong Province, China’s Oldest Nature Reserve

Dinghushan is the only nature reserve at the Tropic of Cancer in mainland China with extensive old growth monsoonal hardwood forest. We here assemble a comprehensive list, with life history notes, of amphibians and reptiles of Dinghushan. Relevant records were scattered over three centuries since the first in 1886. A total of 71 species are known to occur in the reserve, and this number of species per area far exceeds that predicted by classic island biogeographic theory. Among these 71 species, nine are new records: Five frogs (Amolops ricketti, Hylarana macrodactyla, Hylarana taipehensis, Odorrana schmackeri, and Occidozyga lima) and four snakes (Oligodon cinereus, Sinonatrix percarinata, Sinomicrurus macclellandi, and Trimeresurus stejnegeri). One undetermined skink may confound the generic definitions for the genera of Scincella and Sphenomorphus. Among these 71 species, 21 that are not closely associated with old growth forest have not been seen recently. Forest recovery and reforestation of farmland over five decades since the nature reserve was established in 1956 may have contributed to the decline of these species. Dinghushan has 97% of its species occurring strictly in the Oriental zone; among them, about 78% (55) occur both in the South China and Central China regions, 21% (15) occur only in the South China region, and one species was previously known only from the Central China region. The unique location of Dinghushan makes long-term monitoring of its herpetofaunal diversity important for future collaborative studies on a global scale