Agency for Science, Technology and Research

Nanyang Technological University

Future Wei Technologies, Inc.

Ncs Pte, Ltd.

Huawei Technologies Co., Limited

Weisi Lin

Chen-Xiong Zhang

Hai Chen

Susu Yao

Zhongkang Lu

Ee Ping Ong

Susanto Rahardja

Xuan Jing

Zhengguo Li

Xiao Lin

Bu Sung Lee

Arun Kumar Chandran

GuoQing Zhang

Keng Pang Lim

Xiaokang Yang

Chiew Tong Lau

Anmin Liu

Chen Hai

Zhouye Gu

In some aspects, a method for object re-identification may include obtaining a first set of images from a first camera, and a second set of images from at least one second camera; determining a first set of features based on the first set of images, the first set of features lying in a first feature space; and determining a second set of features based on the second set of images, the second set of features lying in a second feature space. The method may additionally include determining a first feature projection matrix and a second feature projection matrix that respectively map the first set of features and the second set of features to a shared feature space; and determining a common dictionary based on the shared feature space.

Object re-identification using multiple cameras

A method is provided for encoding an intra predicted residual block of an image for use in image or video compression. The intra predicted residual block is associated with an intra prediction coding mode. The method includes generating a set of residual error blocks including residual data with different statistical characteristics from the residual data in the intra predicted residual block. Each of the residual error blocks is scanned and entropy coded to produce a first set of bit streams. The lengths of each of the first set of bit streams are recorded. The intra predicted residual block is also scanned and entropy coded to produce a second bit stream. The length of the second bit stream is recorded. Selecting the minimum length bit stream from the first set of bit streams and the second bit stream as the output coded bit stream of the intra predicted residual block.

Lossless image and video compression

A method of performing an image retargeting quality assessment comprising comparing an original image and a retargeted image in a frequency domain, wherein the retargeted image is obtained by performing a retargeting algorithm on the original image. The disclosure also includes an apparatus comprising a processor configured to perform an image retargeting quality assessment, and compare an original image and a retargeted image in a spatial domain, wherein the retargeted image is obtained by performing a retargeting algorithm on the original image, and wherein comparing the original image and the retargeted image in the spatial domain comprises comparing the original image and the retargeted image to determine an amount of shape distortion between the images.

Image retargeting quality assessment

A Method for encoding a picture with a first region and a second region is described wherein the first region is encoded according to a first encoding scheme, the second region is encoded according to a second encoding scheme and the second encoding scheme is carried out taking a parameter representing the visual perception of the second region into account.

Method for encoding a picture, computer program product and encoder

A method of measuring a quality of a test video stream, the method comprising measuring a content richness fidelity feature of the test video stream based on occurrences of color values in image frames of the test video stream; measuring a block-fidelity feature of the test video stream based on distortion at block-boundaries in the image frames of the test video stream; measuring a distortion-invisibility feature of the test video stream based on distortion at pixels of the image frames of the test video stream; and determining a quality rating for the test video stream based on the content richness fidelity feature, the block-fidelity feature and the distortion-invisibility feature measured.

Method and system for video quality measurements

A method for generating a quality oriented significance camp for assessing the quality of an image or video, comprising the steps of extracting features of the image or video, determining a perceptual quality requirement of at least one extracted feature and integrating the extracted features and the perceptual quality requirement of the at least one extracted feature to form an array of significance level values, thereby generating the quality oriented significance map.

Method for generating a quality oriented significance map for assessing the quality of an image or video

Growing community of inventors

Singapore, Singapore

Weisi Lin