Abstract: An object identification method determines whether a first monitoring image and a second monitoring image captured by a monitoring camera apparatus have the same object. The object identification method includes acquiring the first monitoring image at a first point of time to analyze a first object inside a first angle of view of the first monitoring image, acquiring the second monitoring image at a second point of the time different from the first point of time to analyze a second object inside the first angle of view of the second monitoring image, estimating a first similarity between the first object inside the first angle of view of the first monitoring image and the second object inside the first angle of view of the second monitoring image; and determining whether the first object and the second object are the same according to comparison result of the first similarity with a threshold.

Abstract: A camera supporting device includes a supporting frame, an outer casing, a camera holding structure, and a linkage mechanism. The outer casing is rotatably connected to the supporting frame. The camera holding structure is rotatably connected to the supporting frame independently of the outer casing. The linkage mechanism incudes a driving part and a driven part kinematically connected to the driving part. The driving part is fixedly connected to the camera holding structure. The driven part is fixedly connected to the outer casing. An image-capturing device can be fixed on the camera holding structure. Through the camera holding structure driving the outer casing through the linkage mechanism, the outer casing can provide a wider angle range available for the image-capturing device to capturing exterior images.

Abstract: A camera angle detection method is applied to a surveillance apparatus and includes detecting a plurality of straight lines within a surveillance image acquired by the surveillance apparatus, selecting at least one first candidate parallel line and at least one second candidate parallel line from the plurality of straight lines according to a directional trend, stretching the first candidate parallel line and the second candidate parallel line to acquire an intersection point, and computing parameter difference between the intersection point and a reference point of the surveillance image so as to transform the parameter difference to acquire a tilted angle of an optical axis of a lens of the surveillance apparatus relative to a supporting plane where the surveillance apparatus is located.

Abstract: An object identification method is applied to a surveillance system. The surveillance system includes at least one surveillance apparatus. The object identification method includes acquiring a plurality of first feature vectors of a first moving object and a plurality of second feature vectors of at least one second moving object within a series of surveillance images from the surveillance apparatus, transforming the first feature vectors and the second feature vectors respectively into a first cluster distribution set and at least one second cluster distribution set, comparing similarity of the first cluster distribution set and the at least one second cluster distribution set, and setting a similarity ranking of the first cluster distribution set and the at least one second cluster distribution set according to a comparison result so as to determine whether the first moving object and the at least one second moving object are the same.

Abstract: An object counting method is applied to a surveillance camera and used to determine an amount and a direction an object passing over a surveillance region. The object counting method includes acquiring a plurality of known traces, dividing the plurality of known traces into a first group passing the surveillance region along a first direction and a second group passing the surveillance region along a second direction, computing a first start point computed value of the first group and a second start point computed value of the second group to acquire a start point connection vector, and comparing the start point connection vector with a trace vector of a target object to determine whether the target object passes over the surveillance region along the first direction or the second direction.

Abstract: A floor height detection method is applied to a surveillance camera, and a surveillance image captured by the surveillance camera contains a surveillance region. The floor height detection method includes dividing the surveillance image at least into a first region and a second region, acquiring an actual installing height matrix of the surveillance camera upon the first region and the second region, and utilizing a matrix factorization algorithm to analyze the actual installing height matrix to acquire floor heights within the surveillance region.

Abstract: A surveillance region identifying method is used to analyze a region feature of a surveillance region covered by a surveillance apparatus. The surveillance region identifying method includes analyzing all track information within a series of images acquired by the surveillance apparatus to acquire an appearing point and a disappearing point of each track information, utilizing cluster analysis to define a main appearing point cluster of the appearing points, computing enter vectors of all appearing points inside the main appearing point cluster, and analyzing vector angles of all enter vectors of the main appearing point cluster to define an entrance of the surveillance region.

Abstract: An automatic feeding device includes an accommodating container, a transmission channel, a valve unit, a sensor and an ejection unit. The transmission channel is disposed on bottom of the accommodating container. The transmission channel has an inlet portion, a central portion and an outlet portion. The central portion is between the inlet portion and the outlet portion. The valve unit is disposed on the bottom of the accommodating container and adjacent to the inlet portion. The valve unit is switchable to allow feed inside the accommodating container for passing the inlet portion and entering the transmission channel. The sensor is disposed on the inlet portion and detects whether the feed passes the inlet portion, and further outputs a control command to switch modes of the valve unit. The ejection unit is disposed on the central portion and used to push the feed inside the transmission channel toward the outlet portion.

Abstract: A day-mode-night-mode switching method is applied to a monitoring camera apparatus or a filter switching module. The monitoring camera apparatus is electrically connected to an supplemental lighting apparatus for light compensation.

Abstract: An information measuring method is used for measuring installation information of a camera disposed over a plane with an installation height and oriented towards the plane with a shooting angle. The information measuring method includes steps of disposing a first reference point and a second reference point on the plane; measuring a first distance and a second distance between the first reference point, the second reference point and a third reference point; capturing an image including the first reference point, the second reference point and the third reference point; analyzing the image to define a first reference line and a second reference line; determining a first angle and a second angle according to the first reference line, the second reference line and a first normal line; and determining the installation height and/or the shooting angle according to the first distance, the second distance, the first angle and the second angle.

Abstract: An image identifying method is applied to a monitoring camera and a monitoring camera system and used to determine whether a target object is a leaving object or a missing object. The image identifying method includes acquiring a foreground region within a monitoring image corresponding to the target object, analyzing whether the target object inside the foreground region conforms to a variant feature, and comparing the foreground region with a reference image for determining the target object belongs to the leaving object or the missing object when the foreground region does not conform to the variant feature.

Abstract: An exposure compensating method applied to a camera apparatus includes acquiring a monitoring image captured by the camera apparatus via an exposure parameter, computing an estimating exposure compensating value of the monitoring image according to a triggering threshold, analyzing continuity in pixels of the monitoring image with intensity conforming to a specific condition to acquire a weighting adjustment value of a region of interest, adjusting the estimating exposure compensating value via the weighting adjustment value to generate a final exposure compensating value, and adjusting the exposure parameter by the final exposure compensating value.

Abstract: A queue information analyzing method is applied to an image analyzing apparatus. A monitoring image captured by the image analyzing apparatus has a triggering area. The queue information analyzing method includes identifying a first candidate object stayed within the triggering area, forming a sampling range via the first candidate object, determining whether a second candidate object stayed within the sampling range belongs to a queue of the first candidate object, and acquiring an amount and a accumulated time of candidate objects about the queue.

Abstract: A queue analyzing method is applied to an image monitoring apparatus and can automatically generate an interval threshold according to position variation of objects. The queue analyzing method includes computing a plurality of intervals between all objects inside an image, dividing the plurality of intervals at least into a first group corresponding to a low interval range and a second group corresponding to a high interval range, computing an interval mean value and an interval amending value of objects inside the first group, utilizing the interval mean value and the interval amending value to generate the interval threshold, and marking some adjacent objects conforming to the interval threshold within the image.

Abstract: An image calibrating method is applied to a first monitoring image and a second monitoring image partly overlapped with each other. The image calibrating method includes detecting a plurality of first marking points and second marking points about a target object on the first monitoring image and the second monitoring image, computing a first trace and a second trace formed by the first marking points and the second marking points, setting a plurality of first estimating points and second estimating points on stretching sections on the first trace and the second respectively within the second monitoring image and the first monitoring image, and utilizing the first marking points and the second estimating points and/or the first estimating points and the second marking points to compute a shift between the first monitoring image and the second monitoring image.

Abstract: A monitoring camera apparatus includes a main circuit board, a sensing circuit board, an adjusting mechanism and a spiral flexible board. The main circuit board includes an image processor. The sensing circuit board includes an image sensor. The adjusting mechanism is connected to the sensing circuit board for adjusting position of the sensing circuit board and/or a lens of the monitoring camera apparatus, so as to vary a rotary angle and an inclined angle of the sensing circuit board relative to the main circuit board. The spiral flexible board has a first end and a second end opposite to each other. The first end and the second end are respectively connected to the main circuit board and the sensing circuit board, so that image information acquired by the image sensor can be transmitted to the image processor via the spiral flexible board.

Abstract: A queue analyzing method is applied to an image monitoring apparatus for determining whether a rear object belongs to a queue of a front object. The queue analyzing method includes computing an angle difference and an interval between the rear object and the front object, transforming an original interval threshold into an amended interval threshold via the angle difference, comparing the interval with the amended interval threshold, and determining the rear object and the front object belong to the same queue when the interval is smaller than the amended interval threshold.

Abstract: An image stitching method applied to a monitoring camera apparatus with a first image receiver and a second image receiver for acquiring a first image and a second image. The image stitching method includes detecting a plurality of first features in the first image and a plurality of second features in the second image, dividing the plurality of first features at least into a first group and a second group and further dividing the plurality of second features at least into a third group, analyzing the plurality of first features and the plurality of second features via an identification condition to determine whether one of the first group and the second group is matched with the third group, and utilizing two matched groups to stitching the first image and the second image.

Abstract: An image analyzing method of detecting a dimension of a region of interest inside an image is applied to an image analyzing device. The image analyzing method includes positioning an initial triggering pixel unit within a detective identifying area inside the image, and assigning a first detection region via a center of the initial triggering pixel unit, positioning a first based pixel unit conforming to a first target value inside the first detection region, applying a mask via a center of the first based pixel unit to determine whether a first triggering pixel unit exists inside the mask, and utilizing a determination result of the initial triggering pixel unit and the first triggering pixel unit to decide a maximal dimension of the region of interest.