HCI Labs
Speech Image Language Processing Lab.
This HCI lab specially deals with most of the signal processing.
Signals may of of any type, such as Image, Video, Vision, Speech,
EEG, ECG etc...
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6D Mouse
6D Mouse is a low-cost pointing device for use with motion
trackers supporting a serial interface. In addition to its
three prorammable buttons, it contains an embedded DC magnetic
sensor for continuously tracking its positon and orientation
(X, Y, Z, Yaw, Pitch, Roll) in free space. You can use it
as a 3D mouse, an interactive pointer or virtual interface
to real-time visualization systems. |
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Data Gloves
A wired glove is a glove-like input device for human-computer
interaction, often in virtual reality environments. Various
sensor technologies are used to capture physical data such
as bending of fingers. Often a motion tracker, such as a
magnetic tracking device or inertial tracking device, is
attached to capture the global position/rotation data of
the glove. These movements are then interpreted by the software
that accompanies the glove, so any one movement can mean
any number of things. |
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Eye Tracker
An eye tracker is a device for measuring eye positions and
eye movement. Eye trackers are used in research on the visual
system, in psychology, in cognitive linguistics and in product
design. There are a number of methods for measuring eye
movement. The most popular variant uses video images from
which the eye position is extracted. |
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Head Mounted Display
A typical HMD has either one or two small displays with
lenses and semi-transparent mirrors embedded in a helmet,
eye-glasses (also known as data glasses) or visor. The display
units are miniaturised and may include CRT, LCDs, Liquid
crystal on silicon (LCos), or OLED. Some vendors employ
multiple micro-displays to increase total resolution and
field of view. |
Graphics and Visual Computing Lab.
This Lab is equiped with high end graphics processing systems.
CUDA Systems
CUDA or Compute Unified Device Architecture is a parallel computing
architecture developed by Nvidia. CUDA is the computing engine in Nvidia
graphics processing units (GPUs) that is accessible to software developers
through variants of industry standard programming languages. Programmers
use 'C for CUDA' (C with Nvidia extensions and certain restrictions),
compiled through a PathScale Open64 C compiler, to code algorithms for
execution on the GPU. CUDA architecture shares a range of computational
interfaces with two competitors -the Khronos Group's OpenCL and Microsoft's
DirectCompute.
CUDA has several advantages over traditional general purpose computation
on GPUs (GPGPU) using graphics APIs.
Scattered reads – code can read from arbitrary addresses in memory.
Shared memory – CUDA exposes a fast shared memory region (up to
48KB per Multi-Processor) that can be shared amongst threads. This can
be used as a user-managed cache, enabling higher bandwidth than is possible
using texture lookups.
Faster downloads and readbacks to and from the GPU.
Full support for integer and bitwise operations, including integer
texture lookups.