Once sets of mutually orthogonal vanishing points have been detected, it now becomes possible to search for 3D rectangular structures in the image. Over the last decade, a variety of techniques have been developed to find such rectangles, primarily focused on architectural scenes After detecting orthogonal vanishing directions, refine the fitted line equations, search for corners near line intersections, and then verify rectangle hypotheses by rectifying the corresponding patches and looking for a preponderance of horizontal and vertical edges. Detecting and matching features is a significant part of many computer vision systems We’ve explored some practical approaches to detecting features and also discussed how feature correspondences can be established across different images We’ve seen how to implement basic edge and line detectors
explain shortly
It seems like you're describing different techniques and approaches used in computer vision for detecting rectangular structures, orthogonal vanishing points, feature matching, and implementing edge and line detectors. These techniques are crucial in tasks such as scene understanding, object recognition, and 3D reconstruction in computer vision applications. By detecting orthogonal vanishing directions, refining line equations, searching for corners, and verifying rectangle hypotheses, computer vision systems can identify and analyze 3D rectangular structures within images. Additionally, feature detection and matching are essential for establishing correspondences across different images, enabling tasks such as image stitching, object tracking, and visual odometry. These techniques form the foundation for various computer vision applications and are essential for extracting meaningful information from visual data.
While curve approximation with polylines can often lead to successful line extraction, lines in the real world are sometimes broken up into disconnected components or made up of many collinear line segments.
In many cases, it is desirable to group such collinear segments into extended lines.
At a further processing stage, we can then group such lines into collections with common vanishing points.
The Hough transform, named after its original inventor (Hough 1962), is a well-known technique for having edges “vote” for plausible line locations.
• In its original formulation, each edge point votes for all possible lines passing through it, and lines corresponding to high accumulator or bin values are examined for potential line fits (DIA) Unless the points on a line are truly punctate, a better approach (in my experience) is to use the local orientation information at each edgel to vote for a single accumulator cell
Unless the points on a line are truly punctate, a better approach (in my experience) is to use the local orientation information at each edgel to vote for a single accumulator cell (DIA)
A hybrid strategy where each edgel votes for a number of possible orientation or location pairs centered around the estimate orientation, may be desirable in some cases
Since lines are made up of edge segments, we adopt the convention that the line normal ^n points in the same direction (i.e., has the same sign) as the image gradient J(x) = rI(x exp
An alternative representation can be obtained by using a cube map, i.e., projecting m onto the face of a unit cube (Figure 7.63a).
To compute the cube map coordinate of a 3D vector m, first find the largest (absolute value) component of m, i.e., m = max(jnxj; jnyj; jdj), and use this to select one of the six cube faces.
Divide the remaining two coordinates by m and use these as indices into the cube face.
While this avoids the use of trigonometry, it does require some decision logic.
Another alternative to the Hough transform is the RANdom SAmple Consensus (RANSAC) algorithm.
In brief, RANSAC randomly chooses pairs of edgels to form a line hypothesis and then tests how many other edgels fall onto this line.
(If the edge orientations are accurate enough, a single edgel can produce this hypothesis.) Lines with sufficiently large numbers of inliers (matching edgels) are then selected as the desired line segments.
An advantage of RANSAC is that no accumulator array is needed and so the algorithm can be more space efficient and potentially less prone to the choice of bin size.
The disadvantage is that many more hypotheses may need to be generated and tested than those obtained by finding peaks in the accumulator array.
In general, there is no clear consensus on which line estimation technique performs best.
It is therefore a good idea to think carefully about the problem at hand and to implement several approaches (successive approximation, Hough, and RANSAC) to determine the one that works best for your application.
In many scenes, structurally important lines have the same vanishing point because they are parallel in 3D. Examples of such lines are horizontal and vertical building edges, zebra crossings, railway tracks, The first stage in my vanishing point detection algorithm uses a Hough transform to accumulate votes for likely vanishing point candidates.
As with line fitting, one possible approach is to have each line vote for all possible vanishing point directions, either using a cube map or a Gaussian sphere, optionally using knowledge about the uncertainty in the vanishing point location to perform a weighted vote
This has the desirable effect of downweighting (near-)collinear line segments and short line segments
explain shortly
The techniques and methods mentioned in the text are related to the extraction and grouping of lines, vanishing point detection, and line estimation in computer vision. These are fundamental processes in tasks such as scene understanding, 3D reconstruction, and object detection.
The text discusses the challenges of line extraction, such as dealing with broken or fragmented lines, and the desire to group collinear line segments into extended lines. It also mentions the Hough transform as a technique for having edge points "vote" for plausible line locations and the alternative RANdom SAmple Consensus (RANSAC) algorithm for line estimation.
Additionally, the text explains the importance of grouping lines into collections with common vanishing points, which is crucial for understanding the 3D structure of scenes. It also highlights the strategies for vanishing point detection, including the use of Hough transform to accumulate votes for likely vanishing point candidates and the consideration of line orientations and uncertainty in the vanishing point location for weighted voting.
In summary, the text outlines techniques and considerations for line extraction, grouping, vanishing point detection, and line estimation in computer vision, emphasizing the importance of carefully selecting and implementing appropriate approaches for specific applications.
give the name of techniwue used above
The techniques and methods described in the text include the Hough transform for line detection, the RANdom SAmple Consensus (RANSAC) algorithm for line estimation, and the use of weighted voting for vanishing point detection. These techniques are commonly used in computer vision for tasks such as line extraction, line grouping, and vanishing point detection in scenes.
The Hough transform is a feature extraction technique used in image analysis, computer vision, and digital image processing. The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure. This voting procedure is carried out in a parameter space, from which object candidates are obtained as local maxima in a so-called accumulator space that is explicitly constructed by the algorithm for computing the Hough transform. The classical Hough transform was concerned with the identification of lines in the image, but later the Hough transform has been extended to identifying positions of arbitrary shapes, most commonly circles or ellipses. The Hough technique is particularly useful for computing a global description of a feature(s) (where the number of solution classes need not be known a priori), given (possibly noisy) local measurements. The motivating idea behind the Hough technique for line detection is that each input measurement (e.g. coordinate point) indicates its contribution to a globally consistent solution (e.g. the physical line which gave rise to that image point).ex+exp For each data point, a number of lines are plotted going through it, all at different angles. These are shown here in different colours. The Hough transform accumulates contributions from all pixels in the detected edge. To each line, a support line exists which is perpendicular to it and which intersects the origin. In each case, one of these is shown as an arrow. The length (i.e. perpendicular distance to the origin) and angle of each support line is calculated. Lengths and angles are tabulated below the diagrams. From the calculations, it can be seen that in either case the support line at 60° has a similar length. Hence, it is understood that the corresponding lines (the blue ones in the above picture) are very similar. One can thus assume that all points lie close to the blue line. explain sshortly
The Hough transform is a technique used in image analysis and computer vision to identify imperfect instances of certain shapes by a voting procedure. This method involves constructing an accumulator space where local maxima represent the potential instances of the desired shapes. Originally developed for line detection, the Hough transform has been extended to identify positions of arbitrary shapes, such as circles or ellipses.
For line detection using the Hough transform, each input measurement (e.g., coordinate point) contributes to a globally consistent solution, indicating the physical line that corresponds to the image point. This is achieved by plotting a number of lines going through each data point at different angles and accumulating contributions from all pixels in the detected edge. Support lines, perpendicular to the lines going through the data points and intersecting the origin, are calculated based on their length and angle.
In essence, the Hough transform allows for the computation of a global description of features, even when the number of solution classes is not known beforehand, making it particularly useful for handling noisy local measurements and identifying shapes within an image.
tell me shortly how hough transform works for line detection
The Hough transform works for line detection by representing each edge point in an image as a set of potential lines and then accumulating votes for these potential lines in a parameter space. The lines with the most votes correspond to the detected lines in the image. This allows for the identification of imperfect instances of lines in images, making it particularly useful for detecting lines even in the presence of noise or discontinuities.
Given n points in an image, suppose that we want to find subsets of these points that lie on straight lines. One possible solution is to find all lines determined by every pair of points, then find all subsets of points that are close to particular lines. This approach involves finding n(n-1)/2 ∼ n2 lines, then performing (n) n(n-1)/2 ∼ n3 comparisons of every point to all lines. explain shortly
To find subsets of points that lie on straight lines in an image, one approach involves considering all possible lines determined by every pair of points among the given n points. However, this method entails finding approximately n^2 lines and then comparing each point to all lines, resulting in roughly n^3 comparisons overall. While this exhaustive approach is comprehensive, its computational complexity can be quite high, especially for a large number of points.
A proxy ARP is an ARP that acts on behalf of a set of hosts.
Whenever a router running a proxy ARP receives an ARP request looking for the IP address of one of these hosts, the router sends an ARP reply announcing its own hardware (physical) address. After the router receives the actual IP packet, it sends the packet to the appropriate host or router. explain shortly
Proxy ARP is a technique used in computer networking, where a router responds to ARP requests on behalf of other hosts. When the router receives an ARP request for the address of a host it is proxying for, it replies with its own hardware address. This practice allows the router to act as an intermediary for routing packets to the intended destination, effectively extending the reach of the network.
result of a prixy arp
The result of using Proxy ARP is that a router can respond to ARP requests for hosts it is proxying for by providing its own hardware address. This allows the router to facilitate communication between hosts on different subnets or networks, effectively extending the reach of the network without the need for additional routing configurations.
explain shortly Source Device “Generates RARP Request Message” – The source device generates a RARP Request message. The Source puts its own data link-layer address as both the Sender Hardware Address and also the Target Hardware Address. It leaves both the Sender Protocol Address and the Target Protocol Address blank. Source Device “Broadcasts RARP Request Message” – The source broadcasts the ARP Request message on the local network. Local Devices “Process RARP Request Message” – The message is received by each device on the local network and processed. Devices that are not configured to act as RARP servers ignore the message. 4. RARP Server Generates RARP Reply Message: Any device on the network that is a RARP server responds to the broadcast from the source device. It generates a RARP Reply and sets the Sender Hardware Address and Sender Protocol Address to its own hardware and IP address of course. It looks up in a table the hardware address of the source, determines that device’s IP address assignment, and puts it into the Target Protocol Address field. 5. RARP Server Sends RARP Reply Message: The RARP server sends the RARP Reply message unicast to the device looking to be configured. 6. Source Device Processes RARP Reply Message: The source device processes the reply from the RARP server. It then configures itself using the IP address in the Target Protocol Address supplied by the RARP server
In the process of Reverse ARP (RARP), the source device generates a RARP Request message with its own data link-layer address and broadcasts it on the local network. Devices that are not configured as RARP servers ignore the message, while a RARP server generates a RARP Reply message containing the source device's IP address assignment. This reply is unicast to the source device, which configures itself using the IP address provided by the RARP server.
explain shortly Source Device “Generates RARP Request Message” – The source device generates a RARP Request message. The Source puts its own data link-layer address as both the Sender Hardware Address and also the Target Hardware Address. It leaves both the Sender Protocol Address and the Target Protocol Address blank. Source Device “Broadcasts RARP Request Message” – The source broadcasts the ARP Request message on the local network. Local Devices “Process RARP Request Message” – The message is received by each device on the local network and processed. Devices that are not configured to act as RARP servers ignore the message. 4. RARP Server Generates RARP Reply Message: Any device on the network that is a RARP server responds to the broadcast from the source device. It generates a RARP Reply and sets the Sender Hardware Address and Sender Protocol Address to its own hardware and IP address of course. It looks up in a table the hardware address of the source, determines that device’s IP address assignment, and puts it into the Target Protocol Address field. 5. RARP Server Sends RARP Reply Message: The RARP server sends the RARP Reply message unicast to the device looking to be configured. 6. Source Device Processes RARP Reply Message: The source device processes the reply from the RARP server. It then configures itself using the IP address in the Target Protocol Address supplied by the RARP server
In Reverse ARP (RARP), the source device generates a RARP Request message with its own data link-layer address and broadcasts it on the local network. Local devices process the RARP Request message, and if a device on the network is configured as a RARP server, it responds with a RARP Reply message containing the source device's IP address assignment. The RARP server sends this reply unicast to the source device, which then configures itself using the provided IP address.
explain shortly all the points 1.Source Device “Generates RARP Request Message” – The source device generates a RARP Request message. The Source puts its own data link-layer address as both the Sender Hardware Address and also the Target Hardware Address. It leaves both the Sender Protocol Address and the Target Protocol Address blank. 2.Source Device “Broadcasts RARP Request Message” – The source broadcasts the ARP Request message on the local network. 3.Local Devices “Process RARP Request Message” – The message is received by each device on the local network and processed. Devices that are not configured to act as RARP servers ignore the message. 4. RARP Server Generates RARP Reply Message: Any device on the network that is a RARP server responds to the broadcast from the source device. It generates a RARP Reply and sets the Sender Hardware Address and Sender Protocol Address to its own hardware and IP address of course. It looks up in a table the hardware address of the source, determines that device’s IP address assignment, and puts it into the Target Protocol Address field. 5. RARP Server Sends RARP Reply Message: The RARP server sends the RARP Reply message unicast to the device looking to be configured. 6. Source Device Processes RARP Reply Message: The source device processes the reply from the RARP server. It then configures itself using the IP address in the Target Protocol Address supplied by the RARP server
cmp , icmp full form
The full forms of "cmp" and "icmp" are as follows:
CMP: Stands for "Compare." It is a command used in Unix and Unix-like operating systems to compare two files byte by byte and display the differing bytes or lines.
ICMP: Stands for "Internet Control Message Protocol." It is a network layer protocol used to send error and control messages, including the echo request/reply used by the "ping" command.
explain each point very simply Code 0 : network is unreachable, due to hardware failure, can only be generated by a router Code 1 : host is unreachable, due to hardware failure, can only be generated by a router Code 2 : protocol such as UDP, TCP or OSPF is not running at the moment. generated only by the destination Code 3 : the application program (process) that the datagram is destined for is not running at the moment Code 4 : Fragmentation is required, but the DF (do not fragment) field has been set Code 5 : Source routing cannot be accomplished Code 6 : The destination network is unknown. Code 7 : The destination host is unknown. the router is unaware of the existence of the destination Code 8 : The source host is isolated Code 9 : Communication with the destination network is administratively prohibited Code 10 : Communication with the destination host is administratively prohibited Code 11 : the network is unreachable for the specified type of service Code 12 : The host is unreachable for the specified type of service Code 13 : The host is unreachable because the administration has put a filter on it Code 14 : The host is unreachable because the host precedence is violated. The requested precedence is not permitted for the destination Code 15 : The host is unreachable because its precedence was cut off. This message is generated when the network operators have imposed a minimum level of precedence for the operation of the network
explain redirection message format simply
The redirection message format is a simple communication that consists of the following components:
Type of Message: Indicates that the message is a redirection message.
Code: Specifies the reason for the redirection, such as network change or optimal route update.
IP Address: The new IP address or network to which the traffic should be redirected.
Original Packet: Contains information about the original packet that triggered the redirection, including the source and destination IP addresses.
Additional Information: Any additional details or metadata necessary for the recipient to process the redirection effectively.
Overall, the redirection message format serves to inform networking devices about the updated or alternative routes for forwarding packets, optimizing network performance and efficiency.
explain tracert shortly with an example
Tracert (short for "Trace Route") is a command-line tool used to trace the pathway that data takes from one computer to another on a network. It shows the series of network hops (routers) between the source and destination.
Here's an example: When you run "tracert www.example.com" in the command prompt, it will display the route taken by packets from your computer to the website "www.example.com," showing the IP addresses of the routers it passes through and the round-trip times for the packet to reach each router. This information can help diagnose network connectivity issues.
udp,tcp lies in which layer?
UDP (User Datagram Protocol) and TCP (Transmission Control Protocol) reside in the Transport Layer of the OSI (Open Systems Interconnection) model. This layer is responsible for ensuring the reliable transmission of data between network devices, providing error-checking, flow control, and end-to-end connectivity. UDP and TCP are essential protocols for transmitting data over networks and are distinct in their characteristics and functionality.