Object detection system and method

A system for detecting a human in at least one image, the system comprising:

• a processor;
• and
• a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of modules comprising:
• an image capturing module configured to:
• capture at least one image using a motion sensing device, wherein the at least one image comprises a plurality of pixels having gray scale information and a depth information, and wherein the gray scale information comprises intensity of each pixel corresponding to a plurality of objects in the at least one image, and wherein the depth information comprises a distance information between each object and the motion sensing device,
• segment the at least one image into a plurality of segments based on the depth information of the plurality of objects, wherein each segment of the plurality of segments comprises a subset of the plurality of pixels, and each segment corresponds to one or more objects in the at least one image,
• perform a connected component analysis on a segment of the plurality of segments to obtain one or more noisy objects and one or more candidate objects, and
• eliminate the one or more noisy objects from the segment using a vertical pixel projection technique,
• a feature extraction module that is configured to extract a plurality of features from the one or more candidate objects present in the segment, wherein the plurality of features are extracted by,
• applying a windowing technique on the segment in order to divide the segment into one or more blocks, wherein each block of the one or more blocks comprises one or more sub-blocks,
• calculating a local gradient histogram (LGH) corresponding to each sub-block of the one or more sub-blocks, and
• generating a vector comprising the plurality of features by concatenating the LGH of each sub-block;
• and
• an object determination module that is configured to detect a human or a non-human from the one or more candidate objects based on the plurality of features.

A non-transitory computer program product having embodied thereon a computer program for detecting a human in at least one image by performing the step of:

• capturing at least one image using a motion sensing device, wherein the at least one image comprises a plurality of pixels having gray scale information and a depth information, and wherein the gray scale information comprises intensity of each pixel corresponding to a plurality of objects in the at least one image, and wherein the depth information comprises a distance information between each object and the motion sensing device;
• segmenting, by a processor, the at least one image into a plurality of segments based on the depth information of the plurality of objects, wherein each segment of the plurality of segments comprises a subset of the plurality of pixels, and each segment corresponds to one or more objects in the at least one image;
• performing a connected component analysis on a segment of the plurality of segments to obtain one or more noisy objects and one or more candidate objects;
• eliminating the one or more noisy objects from the segment using a vertical pixel projection technique;
• extracting a plurality of features from the one or more candidate objects present in the segment, wherein the plurality of features are extracted by,
• applying a windowing technique on the segment in order to divide the segment into one or more blocks, wherein each block of the one or more blocks comprises one or more sub-blocks,
• calculating a local gradient histogram (LGH) corresponding to each sub-block of the one or more sub-blocks, and
• generating a vector comprising the plurality of features by concatenating the LGH of each sub-block;
• and
• detecting a human or a non-human from the one or more candidate objects based on the plurality of features.