title: Gait analysis of pedestrians with the aim of detecting disabled people

authors: Mukhtar, Amir

abstract: Gait classification is an effective and non-intrusive method for human identification and it has received significant attention in the recent years due to its applications in visual surveillance and monitoring systems. We analyse gait signatures using spatio-temporal motion characteristics of a person to answer the question ``is there a discriminating feature in the gait signal that can help to categorise a disabled person from healthy?''. The procedure has three steps: detection of a pedestrian using YOLO followed by the silhouette extraction using the Gaussian Mixture Model (GMM). Finally, skeletonization from the silhouette image to estimate head and torso locations and their angles with the vertical axis. Furthermore, velocity and acceleration signals were recorded to look for accelerating behaviour of person walking with a limp. Manual segmentations shows that the gait signal has information about unusual walking patterns but existing pedestrian detectors lack accuracy in extracting an accurate gait signal due to localization errors.

text: Gait analysis of pedestrians with the aim of detecting disabled people Gait classification is an effective and non-intrusive method for human identification and it has received significant attention in the recent years due to its applications in visual surveillance and monitoring systems. We analyse gait signatures using spatio-temporal motion characteristics of a person to answer the question ``is there a discriminating feature in the gait signal that can help to categorise a disabled person from healthy?''. The procedure has three steps: detection of a pedestrian using YOLO followed by the silhouette extraction using the Gaussian Mixture Model (GMM). Finally, skeletonization from the silhouette image to estimate head and torso locations and their angles with the vertical axis. Furthermore, velocity and acceleration signals were recorded to look for accelerating behaviour of person walking with a limp. Manual segmentations shows that the gait signal has information about unusual walking patterns but existing pedestrian detectors lack accuracy in extracting an accurate gait signal due to localization errors.

year: 2018

title: Location-based vocabulary learning app

authors: Wu, Shaoqun

subjects: computer science

abstract: This paper presents a mobile app that generates vocabulary learning games based on the user’s geographical location—cinema, restaurant, museum, etc. The app sends the user a notification and offers three fun vocabulary games—Unscramble, Hangman and Matching—when the user enters the premises of the location of interest. This project used cinema halls as the primary location. The games are automatically generated from the movie words and phrases extracted from New York Times movie reviews. The user can either learn new words or review words learned previously. A preliminary study with seven language learners has shown learners’ positive attitude towards the underling principles of location-based vocabulary learning. It has also provided constructive feedback for the future development.

text: Location-based vocabulary learning app This paper presents a mobile app that generates vocabulary learning games based on the user’s geographical location—cinema, restaurant, museum, etc. The app sends the user a notification and offers three fun vocabulary games—Unscramble, Hangman and Matching—when the user enters the premises of the location of interest. This project used cinema halls as the primary location. The games are automatically generated from the movie words and phrases extracted from New York Times movie reviews. The user can either learn new words or review words learned previously. A preliminary study with seven language learners has shown learners’ positive attitude towards the underling principles of location-based vocabulary learning. It has also provided constructive feedback for the future development.

year: 2016

title: E kore koe e ngaro e tōku reo rangatira

authors: Puke, Te Manawanui

subjects: Reo Māori

abstract: Ka whakapeto ngoi ahau ki te wānanga i ngā tini āhuatanga e kōhuru nei, he patu kino nei, e panoni haere nei, e whakamate nei i tōku reo rangatira! E kaha tōmina nei kia kore rawa ai ia e ngaro. Nā reira, ka tīkina te matū o tēnei kaupapa, ka takitaki haere ai mei kore noa e tūpono ka hīnātore mai he māramatanga, he ihumaneatanga i ēnei kōrero āku.

text: E kore koe e ngaro e tōku reo rangatira Ka whakapeto ngoi ahau ki te wānanga i ngā tini āhuatanga e kōhuru nei, he patu kino nei, e panoni haere nei, e whakamate nei i tōku reo rangatira! E kaha tōmina nei kia kore rawa ai ia e ngaro. Nā reira, ka tīkina te matū o tēnei kaupapa, ka takitaki haere ai mei kore noa e tūpono ka hīnātore mai he māramatanga, he ihumaneatanga i ēnei kōrero āku.

year: 2016