Exceptional C++ shows by example how to go about solid software engineering. Along with a lot of other material, this book includes expanded versions of the first 30 issues of the popular Internet C++ feature Guru of the Week (or, in its short form, GotW), a series of self-contained C++ engineering problems and solutions that illustrate specific design and coding techniques.
Specch Recognition system using MATLAB. It includes Viterbi Forwarding and backtracking Algorithm . First it includes feature Extraction and then feature Matching
This Symbian C++ code example demonstrates how to easily use the onboard camera with zoom and autofocus, utilising an accompanying CameraWrapper made by Forum Nokia. The Camera Wrapper supports all Nokia s S60 devices based on S60 3rd Edition and newer, providing a unified interface for various Symbian and S60 camera APIs some of which have previously been feature Pack specific or only available via an SDK plug-in. The example application supports the use of both the keypad and touch UI. The application can be self-signed, but it also provides an option to use the dedicated camera key (Symbian signing required). The example application replaces the separate examples published for S60 3rd Edition, FP1 (S60 Platform: Camera Example with AutoFocus Support v2.2) and FP2 (S60 Camera Example AutoFocus 3rd Ed FP2).
Abstract—The contourlet transform is a new two-dimensional
extension of the wavelet transform using multiscale and direc-
tional fi lter banks. The contourlet expansion is composed of
basis images oriented at various directions in multiple scales,
with fl exible aspect ratios. Given this rich set of basis images,
the contourlet transform effectively captures smooth contours
that are the dominant feature in natural images.
C8051F340/1/2/3/4/5/6/7 devices are fully integrated mixed-signal System-on-a-Chip MCUs. Highlighted
features are listed below. Refer to Table 1.1 for specific product feature selection
sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points.
Among the many features built into Microchip’sEnhanced FLASH Microcontroller devices is the capability of the program memory to self-program. This very useful feature has been deliberately included to give the user the ability to perform bootloading operations.Devices like the PIC18F452 are designed with a designated“boot block”, a small section of protectable program memory allocated specifically for bootload firmware.
Among the many features built into Microchip’sEnhanced FLASH Microcontroller devices is the capability of the program memory to self-program. This very useful feature has been deliberately included to give the user the ability to perform bootloading operations.Devices like the PIC18F452 are designed with a designated“boot block”, a small section of protectable program memory allocated specifically for bootload firmware.
The object detector described below has been initially proposed by
P.F. Felzenszwalb in [Felzenszwalb2010]. It is based on a
Dalal-Triggs detector that uses a single filter on histogram of
oriented gradients (HOG) features to represent an object category.
This detector uses a sliding window approach, where a filter is
applied at all positions and scales of an image. The first
innovation is enriching the Dalal-Triggs model using a
star-structured part-based model defined by a “root” filter
(analogous to the Dalal-Triggs filter) plus a set of parts filters
and associated deformation models. The score of one of star models
at a particular position and scale within an image is the score of
the root filter at the given location plus the sum over parts of the
maximum, over placements of that part, of the part filter score on
its location minus a deformation cost easuring the deviation of the
part from its ideal location relative to the root. Both root and
part filter scores are defined by the dot product between a filter
(a set of weights) and a subwindow of a feature pyramid computed
from the input image. Another improvement is a representation of the
class of models by a mixture of star models. The score of a mixture
model at a particular position and scale is the maximum over
components, of the score of that component model at the given
location.
