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Images for cameras; more images...

Videos, UC QuakeStudies

A video capturing an aftershock from the Canterbury earthquake on 22 February 2011, 1:04pm. After the 6.3 magnitude earthquake at 12:51pm, Ben Post set up his camera on a tripod and left it running. The movement of the water in the fish tank during the quake suggests that the shaking is up and down. The camera also shows this effect; due to the lightweight material of the tripod, the camera is shaken about more than the surroundings.

Videos, UC QuakeStudies

A video capturing an aftershock from the Canterbury earthquake on 13 June 2011, 2:20 pm. A strong shake after lunch time caused Ben Post to set up his camera in his workplace, capturing this aftershock. The camera is mounted on a small sturdy tripod on top of a table with wheels.

Videos, UC QuakeStudies

A video capturing an aftershock from the Canterbury earthquake on 26 December, 10:30 am. After a sharp aftershock in the morning, Ben Post set up the camera on a tripod and kept it running during the morning. The windows shown are approximately three metres square and double glazed.

Images, UC QuakeStudies

People look through the cordon fence at the corner of Colombo and Hereford Streets. On the left is the former site of Camera House, and on the right is the ANZ building, with its ground floor windows boarded up. Taken on a day when a walkway was opened up between Re:Start Mall and Cathedral Square to allow temporary public access.

Audio, Radio New Zealand

The number of speed camera tickets being issued skyrockets, police say it's about road safety, the AA's not so sure. Crisis talks in Europe over the Greek debt crisis... and its impact on the Eurozone and there were angry scenes at a Christchurch meeting last night as residents tried to stop a dump for earthquake debris being built in their suburb.

Videos, UC QuakeStudies

A video about the earthquake damage to the Christchurch Town Hall. The video shows footage of a tour through the inside of the Town Hall, recorded on a GoPro camera. It also includes interviews with Councillor Glenn Livingstone and Councillor Tim Carter about their impressions of the damage and the work that will be needed to fix the building.

Videos, NZ On Screen

This NZBC religious programme goes where TV cameras had never gone before: behind the walls of the Carmelite monastery in Christchurch. There, it finds a community of 16 Catholic nuns, members of a 400-year-old order, who have shut themselves off from the outside world to lead lives devoted to prayer, contemplation and simple manual work. Despite their seclusion, the sisters are unphased by the intrusion and happy to discuss their lives and their beliefs; while the simplicity and ceremony of their world provides fertile ground for the monochrome camerawork.

Images, eqnz.chch.2010

20160703_144759_GT-S7275T-04 New sea wall at Redcliffs (185/366) I went for a drive in my second car mainly to charge the battery up and forgot to take my camera gear so only had my phone. This is the new rock wall to replace the severely damaged previous one (in the February 2011 earthquake). Work is still underway on the car parking and p...

Videos, NZ On Screen

RWP reporter/director Brent Hansen (later head of MTV Europe) visits the South Island: checking venues, talking to local luminaries, catching live bands and generally taking the pulse of the local music scene. Flying Nun is on the rise (and just starting to attract international attention) although none of the label's major acts are playing near the RWP cameras. Christchurch is in flux waiting on the next big pop act to emerge, while Dunedin is a hive of activity with a new generation of Flying Nun acts starting to come through. Then there's Crystal Zoom...

Research papers, University of Canterbury Library

This thesis describes research into developing a client/server ar- chitecture for a mobile Augmented Reality (AR) application. Following the earthquakes that have rocked Christchurch the city is now changed forever. CityViewAR is an existing mobile AR application designed to show how the city used to look before the earthquakes. In CityViewAR 3D virtual building models are overlaid onto video captured by a smartphone camera. However the current version of CityViewAR only allows users to browse information stored on the mobile device. In this research the author extends the CityViewAR application to a client-server model so that anyone can upload models and annotations to a server and have this information viewable on any smartphone running the application. In this thesis we describe related work on AR browser architectures, the system we developed, a user evaluation of the prototype system and directions for future work.

Research papers, University of Canterbury Library

After a high-intensity seismic event, inspections of structural damages need to be carried out as soon as possible in order to optimize the emergency management, as well as improving the recovery time. In the current practice, damage inspections are performed by an experienced engineer, who physically inspect the structures. This way of doing not only requires a significant amount of time and high skilled human resources, but also raises the concern about the inspector’s safety. A promising alternative is represented using new technologies, such as drones and artificial intelligence, which can perform part of the damage classification task. In fact, drones can safely access high hazard components of the structures: for instance, bridge piers or abutments, and perform the reconnaissance by using highresolution cameras. Furthermore, images can be automatically processed by machine learning algorithms, and damages detected. In this paper, the possibility of applying such technologies for inspecting New Zealand bridges is explored. Firstly, a machine-learning model for damage detection by performing image analysis is presented. Specifically, the algorithm was trained to recognize cracks in concrete members. A sensitivity analysis was carried out to evaluate the algorithm accuracy by using database images. Depending on the confidence level desired,i.e. by allowing a manual classification where the alghortim confidence is below a specific tolerance, the accuracy was found reaching up to 84.7%. In the second part, the model is applied to detect the damage observed on the Anzac Bridge (GPS coordinates -43.500865, 172.701138) in Christchurch by performing a drone reconnaissance. Reults show that the accuracy of the damage detection was equal to 88% and 63% for cracking and spalling, respectively.